Professor Steven Schockaert

2025

• Ariyani, N. et al. 2025. There’s no such thing as simple reasoning for LLMs. Presented at: The 63rd Annual Meeting of the Association for Computational Linguistics Vienna, Austria 27 July - 1 August 2025.
• Charpenay, V. and Schockaert, S. 2025. Less Is MuRE: Revisiting shallow knowledge graph embeddings. Presented at: The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP) Suzhou, China 4-9 November 2025.
• Das, A. et al. 2025. When no paths lead to Rome: Benchmarking systematic neural relational reasoning. Presented at: The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS) San Diego, USA 02-07 December 2025.
• Gajbhiye, A. et al. 2025. Grouping entities with shared properties using multi-facet prompting and property embeddings. Presented at: The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP) Suzhou, China 4-9 November 2025.
• Khalid, M. , Nourollah, A. M. and Schockaert, S. 2025. Large language and reasoning models are shallow disjunctive reasoners. Presented at: The 63rd Annual Meeting of the Association for Computational Linguistics Vienna, Austria 27 July - 1 August 2025.
• Khalid, M. and Schockaert, S. 2025. Systematic relational reasoning with epistemic graph neural networks. Presented at: The Thirteenth International Conference on Learning Representation Singapore 24-28 April 2025. The Thirteenth International Conference on Learning Representation.
• Kumar, N. , Chatterjee, U. and Schockaert, S. 2025. Extracting conceptual spaces from LLMs using prototype embeddings. Presented at: Findings of EMNLP Suzhou, China 4-9 November 2025.
• Pavlovic, A. , Sallinger, E. and Schockaert, S. 2025. Faithful differentiable reasoning with reshuffled region-based embeddings. Presented at: 22nd International Conference on Principles of Knowledge Representation and Reasoning (KR 2025) Melbourne, Australia 11-17 November 2025. Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning. International Joint Conferences on Artificial Intelligence Organization. , pp.489-499. (10.24963/kr.2025/48)
• Ushio, A. , Camacho Collados, J. and Schockaert, S. 2025. RelBERT: Embedding relations with language models. Artificial Intelligence 347 104359. (10.1016/j.artint.2025.104359)
• Yan, K. et al., 2025. Modelling multi-modal cross-interaction for multi-label few-shot image classification based on local feature selection. ACM Transactions on Multimedia Computing, Communications and Applications 21 (3) 80. (10.1145/3711867)

2024

• Akash Anil, A. et al. 2024. Inductive knowledge graph completion with GNNs and rules: An analysis. Presented at: 2024 Joint International Conference On Computational Linguistics, Language Resources And Evaluation (LREC-COLING 2024) Turin, Italy 20-25 May 2024. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation. ELRA and ICCL. , pp.9036-9049.
• Almeman, F. , Schockaert, S. and Espinosa-Anke, L. 2024. WordNet under scrutiny: Dictionary examples in the era of large language models. Presented at: The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING) Torino, Italy 20-24 May 2024. Published in: Calzolari, N. et al., Main conference proceedings of the Joint International Conference on Computational Linguistics, Language Resources and Evaluation. ELRA. , pp.17683-17695.
• Ariyani, N. et al. 2024. Can language models learn embeddings of propositional logic assertions?. Presented at: The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING) Turin, Italy 20-25 May 2024. Published in: Calzolari, N. et al., Proceedings of Joint International Conference on Computational Linguistics, Language Resources and Evaluation. European Language Resources Association. , pp.2766-2776.
• Baaj, I. et al., 2024. Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems 171 109206. (10.1016/j.ijar.2024.109206)
• Charpenay, V. and Schockaert, S. 2024. Capturing knowledge graphs and rules with octagon embeddings. Presented at: 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024) Jeju, South Korea 3-9 August 2024. Published in: Larson, K. ed. Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence. , pp.3289-3297. (10.24963/ijcai.2024/364)
• Es, S. et al., 2024. RAGAs: Automated evaluation of retrieval augmented generation. Presented at: The 18th Conference of the European Chapter of the Association for Computational Linguistics (System Demonstrations) St Julian's, Malta 17-22 March 2024. Published in: Aletras, N. and De Clercq, O. eds. Proceedings of the EACL 2024. , pp.150-158.
• Gajbhiye, A. et al. 2024. AMenDeD: Modelling concepts by aligning mentions, definitions and decontextualised embeddings. Presented at: The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING) Torino, Italy 20-25 May 2024. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation. European Language Resources Association. , pp.801-811.
• Kteich, H. et al., 2024. Modelling commonsense commonalities with multi-facet concept embeddings. Presented at: The 62nd Annual Meeting of the Association for Computational Linguistics Bangkok, Thailand 11-16 August 2024. Published in: Ku, L. , Martins, A. and Srikumar, V. eds. Findings of the Association for Computational Linguistics ACL 2024. Association for Computational Linguistics. , pp.1467-1480. (10.18653/v1/2024.findings-acl.86)
• Kumar, N. , Chatterjee, U. and Schockaert, S. 2024. Ranking entities along conceptual space dimensions with LLMs: An analysis of fine-tuning strategies. Presented at: The 62nd Annual Meeting of the Association for Computational Linguistics Bangkok, Thailand 11-16 August 2024. Published in: Ku, L. , Martins, A. and Srikumar, V. eds. Findings of the Association for Computational Linguistics ACL 2024. Association for Computational Linguistics. , pp.7974-7989. (10.18653/v1/2024.findings-acl.474)
• Mtumbuka, F. and Schockaert, S. 2024. EnCore: fine-grained entity typing by pre-training entity encoders on coreference chains. Presented at: The 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL) St Julian's, Malta 17-22 March 2024. Published in: Graham, Y. and Purver, M. eds. Vol. 1.Association for Computational Linguistics. , pp.1768-1781.
• Mtumbuka, F. and Schockaert, S. 2024. Entity or relation embeddings? An analysis of encoding strategies for relation extraction. Presented at: Findings of EMNLP
• Na, L. et al., 2024. CONTOR: Benchmarking strategies for completing ontologies with plausible missing rules. Presented at: Findings of EMNLP Miami, Florida 12-16 November 2024.
• Schockaert, S. 2024. Embeddings as epistemic states: Limitations on the use of pooling operators for accumulating knowledge. International Journal of Approximate Reasoning: Uncertainty in Intelligent Systems 171 108981. (10.1016/j.ijar.2023.108981)
• Ushio, A. , Camacho Collados, J. and Schockaert, S. 2024. A RelEntLess benchmark for modelling graded relations between named entities. Presented at: The 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL) St Julian's, Malta 17-22 March 2024. Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics. Vol. 1.Association for Computational Linguistics. , pp.2473-2486.

2023

• Chatterjee, U. , Gajbhiye, A. and Schockaert, S. 2023. Cabbage sweeter than cake? Analysing the potential of large language models for learning conceptual spaces. Presented at: Conference on Empirical Methods in Natural Language Processing, EMNLP Singapore 6-10 December 2023. Published in: Bouamor, H. , Pino, J. and Bali, K. eds. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. , pp.11836–11842. (10.18653/v1/2023.emnlp-main.725)
• Chatterjee, U. and Schockaert, S. 2023. Probing the conceptual space of ChatGPT and GPT-4. Presented at: 9th Workshop on Artificial Intelligence and Cognition Bremen 14-15 September 2023.
• Doval, Y. et al., 2023. Meemi: a simple method for post-processing and integrating cross-lingual word embeddings. Natural Language Engineering 29 (3), pp.746-768. (10.1017/S1351324921000280)
• Gajbhiye, A. et al. 2023. What do deck chairs and sun hats have in common? Uncovering shared properties in large concept vocabularies. Presented at: Conference on Empirical Methods in Natural Language Processing, EMNLP Singapore 6-10 December 2023. Published in: Bouamor, H. , Pino, J. and Bali, K. eds. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. , pp.10587–10596. (10.18653/v1/2023.emnlp-main.654)
• Kumar, N. and Schockaert, S. 2023. Solving hard analogy questions with relation embedding chains. Presented at: Conference on Empirical Methods in Natural Language Processing, EMNLP Singapore 6-10 December 2023. Published in: Bouamor, H. , Pino, J. and Bali, K. eds. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. , pp.6224–6236. (10.18653/v1/2023.emnlp-main.382)
• Li, N. , Bouraoui, Z. and Schockaert, S. 2023. Ultra-fine entity typing with prior knowledge about labels: a simple clustering based approach. Presented at: Findings of the Association for Computational Linguistics: EMNLP 2023 Singapore December 2023. Published in: Bouamor, H. , Pino, J. and Bali, K. eds. Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics. , pp.11744–11756. (10.18653/v1/2023.findings-emnlp.786)
• Li, N. et al., 2023. Distilling semantic concept embeddings from contrastively fine-tuned language models. Presented at: 46th International ACM SIGIR Conference on Research and Development in Information Retrieval Taipei, Taiwan 23-27 July 2023. Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. , pp.216. (10.1145/3539618.3591667)
• Tedeschi, S. et al., 2023. What's the meaning of superhuman performance in today's NLU?. Presented at: The 61st Annual Meeting of the Association for Computational Linguistics (ACL’23) Toronto, Canada 9-14 July 2023. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics. Vol. 1.Association for Computational Linguistics. , pp.12471-12491. (10.18653/v1/2023.acl-long.697)

2022

• Alghanmi, I. , Espinosa-Anke, L. and Schockaert, S. 2022. Interpreting patient descriptions using distantly supervised similar case retrieval. Presented at: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 11-15 July 2022. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). ACM. , pp.460-470. (10.1145/3477495.3532003)
• Alghanmi, I. , Espinosa-Anke, L. and Schockaert, S. 2022. Self-supervised intermediate fine-tuning of biomedical language models for interpreting patient case descriptions. Presented at: 29th International Conference on Computational Linguistics (COLING) Gyeongju, Republic of Korea 12-17 October 2022. Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics
• Bouraoui, Z. , Gutierrez Basulto, V. and Schockaert, S. 2022. Integrating ontologies and vector space embeddings using conceptual spaces. Presented at: International Research School in Artificial Intelligence in Bergen (AIB 2022) 7-11 June 2022. The OpenAccess Series in Informatics. Vol. 99.Open Access Series in Informatics (OASIcs) Dagstuhl, Germany: Dagstuhl Publishing. , pp.3:1-3:30. (10.4230/OASIcs.AIB.2022.3)
• Gajbhiye, A. , Espinosa-Anke, L. and Schockaert, S. 2022. Modelling commonsense properties using pre-trained bi-encoders. Presented at: 29th International Conference on Computational Linguistics (COLING) 12-17 October 2022. Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics. , pp.3971-3983.
• Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2022. Pre-training language models for identifying patronizing and condescending language: an analysis. Presented at: LREC 2022 Marseille; France 20-25 June 2022. Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association. , pp.3902-3911.
• Perez Almendros, C. and Schockaert, S. 2022. Identifying condescending language: a tale of two distinct phenomena?. Presented at: Second Workshop on NLP for Positive Impact (NLP4PI) Abu Dhabi, United Arab Emirates (Hybrid) 7 December 2022. Published in: Biester, L. et al., Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI). Association for Computational Linguistics. , pp.130–141. (10.18653/v1/2022.nlp4pi-1.15)
• Perez-Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2022. SemEval-2022 task 4: patronizing and condescending language detection. Presented at: 16th International Workshop on Semantic Evaluation (SemEval-2022) Seattle, United States July 2022. Published in: Emerson, G. et al., Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). Association for Computational Linguistics. , pp.298–307. (10.18653/v1/2022.semeval-1.38)
• Perez-Almendros, C. and Schockaert, S. 2022. Identifying condescending language: A tale of two distinct phenomena?. Presented at: Workshop on NLP for Positive Impact UAE 7 December 2022.
• Wang, Y. et al. 2022. Sentence selection strategies for distilling word embeddings from BERT. Presented at: LREC 2022 Marseille, France 20-25 June 2022. Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA). , pp.2591-2600.
• Yan, K. et al., 2022. Inferring prototypes for multi-label few-shot image classification with word vector guided attention. Presented at: 36th AAAI Conference on Artificial Intelligence Vancouver, BC, Canada 22 February - 01 March 2022. Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 36(3).Association for the Advancement of Artificial Intelligence. , pp.2991-2999. (10.1609/aaai.v36i3.20205)

2021

• Alghanmi, I. , Espinosa-Anke, L. and Schockaert, S. 2021. Probing pre-trained language models for disease knowledge. Findings 2021 (August), pp.3023-3033. (10.18653/v1/2021.findings-acl.266)
• Ito, T. et al., 2021. Learning company embeddings from annual reports for fine-grained industry characterization. Presented at: FinNLP-2020 Kyoto, Japan 11-13 July 2020. Published in: Chen, C. -. et al., Proceedings of the Second Workshop on Financial Technology and Natural Language Processing. , pp.27-33.
• Li, N. et al., 2021. Modelling general properties of nouns by selectively averaging contextualised embeddings. Presented at: 30th International Joint Conference on Artificial Intelligence (IJCAI 2021) Virtual 21-26 August 2021.
• Schockaert, S. 2021. Modelling monotonic and non-monotonic attribute dependencies with embeddings: a theoretical analysis. Presented at: 3rd Conference on Automated Knowledge Base Construction (AKBC 2021) Virtual 4-8 October 2021.
• Schockaert, S. and Gutierrez Basulto, V. 2021. Modelling symbolic knowledge using neural representations. Presented at: Reasoning Web Summer School 2021 Leuven, Belgium 8-15 September 2021. Reasoning Web. Lecture Notes in Computer Science Springer. , pp.59-75. (10.1007/978-3-030-95481-9_3)
• Schockaert, S. , Ibanez Garcia, Y. and Gutierrez Basulto, V. 2021. A description logic for analogical reasoning. Presented at: 30th International Joint Conference on Artificial Intelligence (IJCAI 2021) Virtual 21-26 August 2021. Published in: Zhou, Z. ed. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization. , pp.2040-2046. (10.24963/ijcai.2021/281)
• Schockaert, S. , Ibanez Garcia, Y. and Gutierrez Basulto, V. 2021. Modelling concept interpolation in description logics using abstract betweenness relations. Presented at: 34th International Workshop on Description Logics (DL 2021) Bratislava, Slovakia 19-22 September 2021.
• Ushio, A. , Camacho Collados, J. and Schockaert, S. 2021. Distilling relation embeddings from pre-trained language models. Presented at: 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP) Punta Cana, Dominican Republic 7-11 November 2021. Published in: Moens, M. et al., Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. , pp.9044-9062. (10.18653/v1/2021.emnlp-main.712)
• Ushio, A. et al. 2021. BERT is to NLP what AlexNet is to CV: can pre-trained language models identify analogies?. Presented at: 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) Bangkok, Thailand 1-6 August 2021.
• Wang, Y. et al. 2021. Deriving word vectors from contextualized language models using topic-aware mention selection. Presented at: 6th Workshop on Representation Learning for NLP (RepL4NLP 2021) Virtual / Bangkok, Thailand 05 August 2021. Proceedings of the 6th Workshop on Representation Learning for NLP. Association for Computational Linguistics. , pp.185-194. (10.18653/v1/2021.repl4nlp-1.19)
• Yan, K. et al., 2021. Aligning visual prototypes with BERT embeddings for few-shot learning. Presented at: ACM International Conference on Multimedia Retrieval (ACM ICMR 2021) Taipei, Taiwan 21-24 August 2021. Proceedings of the 2021 International Conference on Multimedia Retrieval. New York, NY, USA: Association for Computing Machinery. , pp.367-375. (10.1145/3460426.3463641)
• Yan, K. et al., 2021. Few-shot image classification with multi-facet prototypes. Presented at: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021) Toronto, ON, Canada 6-11 June 2021. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. , pp.1740-1744. (10.1109/ICASSP39728.2021.9414374)

2020

• Alghanmi, I. , Espinosa-Anke, L. and Schockaert, S. 2020. Combining BERT with static word embeddings for categorizing social media. Presented at: 6th Workshop on Noisy User-generated Text (W-NUT 2020) Virtual 19 November 2020.
• Alshaikh, R. et al. 2020. A mixture-of-experts model for learning multi-facet entity embeddings. Presented at: The 28th International Conference on Computational Linguistics (COLING 2020) Virtual 8-13 December 2020. Published in: Scott, D. , Bel, N. and Zong, C. eds. Proceedings of the 28th International Conference on Computational Linguistics. Association for Computational Linguistics. , pp.5124-5135. (10.18653/v1/2020.coling-main.449)
• Alshaikh, R. , Bouraoui, Z. and Schockaert, S. 2020. Hierarchical linear disentanglement of data-driven conceptual spaces. Presented at: International Joint Conferences on Artificial Intelligence Organization (IJCAI-PRICAI 2020) Yokohama, Japan 11-17 July 2020. Published in: Bessiere, C. ed. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. , pp.3573-3579. (10.24963/ijcai.2020/494)
• Bouraoui, Z. et al., 2020. Modelling semantic categories using conceptual neighborhood. Presented at: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) New York, NY, USA 7-12 February 2020. Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 34(05).PKP Publishing Services. , pp.7448-7455. (10.1609/aaai.v34i05.6241)
• Bouraoui, Z. , Camacho Collados, J. and Schockaert, S. 2020. Inducing relational knowledge from BERT. Presented at: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) New York, NY, USA 7-12 February 2020. Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 34.Vol. 5. , pp.7456-7463. (10.1609/aaai.v34i05.6242)
• Camacho Collados, J. et al. 2020. Learning cross-lingual word embeddings from Twitter via distant supervision. Proceedings of the International AAAI Conference on Web and Social Media 14 (1), pp.72-82.
• Ibanez Garcia, Y. , Gutierrez Basulto, V. and Schockaert, S. 2020. Plausible reasoning about EL-Ontologies using concept interpolation. Presented at: 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020) Rhodes, Greece 12-18 September 2020. Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning. IJCAI Organization. , pp.506-516. (10.24963/kr.2020/51)
• Jeawak, S. , Jones, C. and Schockaert, S. 2020. Predicting environmental features by learning spatiotemporal embeddings from social media. Ecological Informatics 55 101031. (10.1016/j.ecoinf.2019.101031)
• Jeawak, S. S. , Espinosa-Anke, L. and Schockaert, S. 2020. Cardiff University at SemEval-2020 Task 6: fine-tuning BERT for domain-specific definition classification. Presented at: International Workshop on Semantic Evaluation (SemEval 2020) Barcelona, Spain 12-13 December 2020. Published in: Herbelot, A. et al., Proceedings of the Fourteenth International Workshops on Semantic Evaluation, SemEval 2020 - co-located 28th International Conference on Computational Linguistics. International Committee for Computational Linguistics. , pp.361-366.
• Jeawak, S. S. , Jones, C. B. and Schockaert, S. 2020. Predicting the environment from social media: a collective classification approach. Computers, Environment and Urban Systems 82 (10.1016/j.compenvurbsys.2020.101487)
• Lee, J. H. et al. 2020. Capturing word order in averaging based sentence embeddings. Presented at: European Conference on Artificial Intelligence (ECAI2020) Santiago de Compostela, Spain 29 August - 2 September 2020. Published in: De Giacomo, G. et al., 24th European Conference on Artificial Intelligence. Vol. 325.IOS Press. , pp.2062-2069. (10.3233/FAIA200328)
• Mushthofa, M. , Schockaert, S. and De Cock, M. 2020. Fuzzy answer set programming: from theory to practice. In: Kosheleva, O. et al., Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications. Vol. 835, Studies in Computational Intelligence Springer. , pp.213–228. (10.1007/978-3-030-31041-7_12)
• Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2020. Don’t patronize me! An annotated dataset with patronizing and condescending language towards vulnerable communities. Presented at: 28th International Conference on Computational Linguistics (COLING) Barcelona, Spain 13-18 December 2020. Published in: Scott, D. , Bel, N. and Zong, C. eds. Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics. , pp.5891–5902. (10.18653/v1/2020.coling-main.518)
• Pérez-Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2020. Don't patronize me! An annotated dataset with patronizing and condescending language towards vulnerable communities. Presented at: The 28th International Conference on Computational Linguistics (COLING 2020) Virtual 8-13 December 2020.
• Svatoš, M. et al., 2020. STRiKE: Rule-driven relational learning using stratified k-entailment. Presented at: European Conference on Artificial Intelligence (ECAI2020) Santiago de Compostela, Spain 29 August - 2 September. Published in: De Giacomo, G. et al., Proceedings of the 24th European Conference on Artificial Intelligence. Vol. 325.IOS Press. , pp.1515-1522. (10.3233/FAIA200259)

2019

• Alshaikh, R. , Bouraoui, Z. and Schockaert, S. 2019. Learning conceptual spaces with disentangled facets. Presented at: CoNLL 2019: The SIGNLL Conference on Computational Natural Language Learning Hong Kong, China 3-4 November 2019.
• Bouraoui, Z. and Schockaert, S. 2019. Automated rule base completion as Bayesian concept induction. Presented at: AAAI-2019: 33rd AAAI Conference on Artificial Intelligence Honololu, HI, USA 27 January - 1 February 2019. Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33.Vol. 1. Palo Alto, California: AAAI Press. , pp.6228-6235. (10.1609/aaai.v33i01.33016228)
• Camacho Collados, J. et al. 2019. A latent variable model for learning distributional relation vectors. Presented at: IJCAI-19: International Joint Conference on Artificial Intelligence Macau, China 10-16 August 2019. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence Main track. IJCAI. , pp.4911-4917. (10.24963/ijcai.2019/682)
• Camacho Collados, J. , Espinosa-Anke, L. and Schockaert, S. 2019. Relational word embeddings. Presented at: 57th Annual Meeting of the Association for Computational Linguistics (ACL) Florence, Italy 28 July - 2 August 2019. Published in: Korhonen, A. , Traum, D. and Marquez, L. eds. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. , pp.3286-3296.
• Espinosa-Anke, L. , Schockaert, S. and Wanner, L. 2019. Collocation classification with unsupervised relation vectors. Presented at: 57th Annual Meeting of the Association for Computational Linguistics (ACL) Florence, Italy 28 July - 2 August 2019. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. , pp.5765-5772. (10.18653/v1/P19-1576)
• Jameel, S. et al. 2019. Word embedding as maximum a posteriori estimation. Presented at: AAAI-19: 33rd AAAI Conference on Artificial Intelligence Honolulu, HI, USA 27 January - 1 February 2019. Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33.Vol. 1. Palo Alto, California: AAAI Press. , pp.6562-6569. (10.1609/aaai.v33i01.33016562)
• Jameel, S. and Schockaert, S. 2019. Word and document embedding with vMF-mixture priors on context word vectors. Presented at: 57th Annual Meeting of the Association for Computational Linguistics (ACL) Florence, Italy 28 July - 2 August 2019. Published in: Korhornen, A. , Traum, D. and Marquez, L. eds. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy: Association for Computational Linguistics. , pp.3319-3328. (10.18653/v1/P19-1321)
• Jeawak, S. , Jones, C. and Schockaert, S. 2019. Embedding geographic locations for modelling the natural environment using Flickr tags and structured data. Presented at: ECIR 2019: 41st European Conference on Information Retrieval Cologne, Germany 14-18 April 2019. , pp.-.
• Kuzelka, O. , Wang, Y. and Schockaert, S. 2019. VC-dimension based generalization bounds for relational learning. Presented at: ECML-PKDD 2018: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Dublin, Ireland 10-14 Sept 2018. Published in: Berlingerio, M. et al., Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vol. 11052.Lecture Notes in Computer Science Springer. , pp.259-275. (10.1007/978-3-030-10928-8_16)
• Li, N. , Bouraoui, Z. and Schockaert, S. 2019. Ontology completion using graph convolutional networks. Presented at: 18th International Semantic Web Conference Auckland, New Zealand 26-30 October 2019. Published in: Ghidini, C. et al., The Semantic Web – ISWC 2019. Lecture Notes in Computer Science Springer. , pp.435–452. (10.1007/978-3-030-30793-6_25)
• Perez Almendros, C. , Espinosa-Anke, L. and Schockaert, S. 2019. Cardiff University at SemEval-2019 Task 4: Linguistic features for hyperpartisan news detection. Presented at: SemEval-2019: International Workshop on Semantic Evaluation Minneapolis, Minnesota, USA 6-7 June 2019. Association for Computational Linguistics. , pp.929-933. (10.18653/v1/S19-2158)
• Zhou, Y. , Schockaert, S. and Shah, J. A. 2019. Predicting ConceptNet path quality using crowdsourced assessments of naturalness. Presented at: The Web Conference 2019 San Francisco, CA, USA 13-17 May 2019.
• Zhou, Y. , Shah, J. A. and Schockaert, S. 2019. Learning household task knowledge from WikiHow descriptions. Presented at: 5th Workshop on Semantic Deep Learning Macau, China 10-16 August 2019. Published in: Espinosa-Anke, L. et al. Proceedings of the 5th Workshop on Semantic Deep Learning (SemDeep-5). Association for Computational Linguistics. , pp.50-56.

2018

• Ager, T. , Kuzelka, O. and Schockaert, S. 2018. Modelling salient features as directions in fine-tuned semantic spaces. Presented at: SIGNLL Conference on Computational Natural Language Learning Brussels, Belgium 31 Oct - 1 Nov 2018.
• Barbieri, F. et al., 2018. Interpretable Emoji prediction via label-wise attention LSTM's. Presented at: Conference on Empirical Methods in Natural Language Processing Brussels 31 October-4 November.
• Bouraoui, Z. , Jameel, M. and Schockaert, S. 2018. Relation induction in word embeddings revisited. Presented at: 27th International Conference on Computational Linguistics (COLING 2018) Santa Fe, NM, USA 20-26 August 2018.
• Bouraoui, Z. and Schockaert, S. 2018. Learning conceptual space representations of interrelated concepts. Presented at: 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI-18) Stockholm, Sweden 13-19 July 2018. Published in: Lang, J. ed. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization. , pp.1760-1766. (10.24963/ijcai.2018/243)
• De Clercq, S. et al., 2018. Modelling incomplete information in Boolean games using possibilistic logic. International Journal of Approximate Reasoning 93 , pp.1-23. (10.1016/j.ijar.2017.10.017)
• Doval, Y. et al., 2018. Improving cross-lingual word embeddings by meeting in the middle. Presented at: Conference on Empirical Methods in Natural Language Processing Brussels 31 October-4 November.
• Espinosa-Anke, L. and Schockaert, S. 2018. SeVeN: Augmenting word embeddings with unsupervised relation vectors. Presented at: 27th International Conference on Computational Linguistics (COLING 2018) Santa Fe, NM, USA 20-26 August 2018.
• Espinosa-Anke, L. and Schockaert, S. 2018. Syntactically aware neural architectures for definition extraction. Presented at: 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies New Orleans 1-6 June 2018.
• Gutierrez Basulto, V. and Schockaert, S. 2018. From knowledge graph embedding to ontology embedding? An analysis of the compatibility between vector space representations and rules. Presented at: 16th International Conference on Principles of Knowledge Representation and Reasoning Tempe, Arizona 27 Oct - 2 Nov 2018.
• Jameel, M. , Bouraoui, Z. and Schockaert, S. 2018. Unsupervised learning of distributional relation vectors. Presented at: 56th Annual Meeting of the Association for Computational Linguistics Melbourne, Australia 15-20 July 2018.
• Jeawak, S. , Jones, C. and Schockaert, S. 2018. Mapping wildlife species distribution with social media: Augmenting text classification with species names. Presented at: GIScience 2018: 10th International Conference on Geographic Information Science Melbourne, Australia 28-31 August 2018. Published in: Winter, S. , Griffin, A. and Sester, M. eds. 10th International Conference of Geographic Information Science (GIScience 2018). Vol. 114.Leibniz International Proceedings in Informatics (LIPIcs) Dagstuhl, Germany: Schloss Dagstuhl/Leibniz-Zentrum fuer Informatik. , pp.34:1-34:6. (10.4230/LIPIcs.GISCIENCE.2018.34)
• Kuzelka, O. et al. 2018. PAC-reasoning in relational domains. Presented at: UAI2018: 34th Conference on Uncertainty in Artificial Intelligence Monterey, CA, USA 6-10 August 2018. Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence. AUAI Press. , pp.927 - 936.
• Kuzelka, O. et al., 2018. Relational marginal problems: theory and estimation. Presented at: 32nd AAAI Conference on Artificial Intelligence New Orleans, USA 2-7 February 2018.
• Mushthofa, M. et al., 2018. Modeling multi-valued biological interaction networks using Fuzzy Answer Set Programming. Fuzzy Sets and Systems 345 , pp.63-82. (10.1016/j.fss.2018.01.003)
• Schockaert, S. and Li, S. 2018. Reasoning about betweenness and RCC8 constraints in qualitative conceptual spaces. Presented at: 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI-18) Stockholm, Sweden 13-19 July 2018. Published in: Lang, J. ed. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization. , pp.1963-1969. (10.24963/ijcai.2018/271)
• Sourek, G. et al., 2018. Lifted relational neural networks: efficient learning of latent relational structures. Journal of Artificial Intelligence Research 62 , pp.69-100. (10.1613/jair.1.11203)
• Sourek, G. et al., 2018. Stacked structure learning for lifted relational neural networks. Presented at: International Conference on Inductive Logic Programming Orléans, France 4- 6 September 2017. Published in: Lachiche, N. and Vrain, C. eds. Inductive Logic Programming. Lecture Notes in Computer Science Vol. 10759. Springer. , pp.140-151. (10.1007/978-3-319-78090-0_10)

2017

• Bouraoui, Z. , Jameel, S. and Schockaert, S. 2017. Inductive reasoning about ontologies using conceptual spaces. Presented at: 31st AAAI Conference on Artificial Intelligence San Francisco, CA, USA 4-9 February 2017. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. AAAI Press. , pp.4364-4370. (10.5555/3298023.3298201)
• De Clercq, S. et al., 2017. Exact and heuristic methods for solving Boolean games. Autonomous Agents and Multi-Agent Systems 31 (1), pp.66-106. (10.1007/s10458-015-9313-5)
• Dubois, D. , Prade, H. and Schockaert, S. 2017. Generalized possibilistic logic: foundations and applications to qualitative reasoning about uncertainty. Artificial Intelligence 252 , pp.139-174. (10.1016/j.artint.2017.08.001)
• Jameel, S. , Bouraoui, Z. and Schockaert, S. 2017. MEmbER: Max-Margin Based Embeddings for Entity Retrieval. Presented at: 40th International ACM SIGIR Conference on Research and Development in Information Retrieval Tokyo, Japan 7-11 August 2017. SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: Association for Computing Machinery. , pp.783-792. (10.1145/3077136.3080803)
• Jameel, S. and Schockaert, S. 2017. Modeling context words as regions: an ordinal regression approach to word embedding. Presented at: SIGNLL Conference on Computational Natural Language Learning Vancouver, Canada 3-4 August 2017. Published in: Levy, R. and Specia, L. eds. Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017). Association of Computing Language. , pp.123-133. (10.18653/v1/K17-1014)
• Jeawak, S. , Jones, C. B. and Schockaert, S. 2017. Using Flickr for characterizing the environment: an exploratory analysis. Presented at: 13th International Conference on Spatial Information Theory (COSIT) L’Aquila, Italy 4-8 September 2017. 13th International Conference on Spatial Information Theory (COSIT 2017). Leibniz International Proceedings in Informatics. , pp.21:1-21:13. (10.4230/LIPIcs.COSIT.2017.21)
• Kuzelka, O. , Davis, J. and Schockaert, S. 2017. Induction of interpretable possibilistic logic theories from relational data. Presented at: International Joint Conference on Artificial Intelligence (IJCAI) Melbourne, Australia 19-26 August 2017.
• Kuzelka, O. , Davis, J. and Schockaert, S. 2017. Learning possibilistic logic theories from default rules (abridged version). Presented at: IJCAI-17: Workshop on Logical Foundations for Uncertainty and Machine Learning Melbourne, Australia 19-25 August 2017.
• Merhej, E. , Schockaert, S. and De Cock, M. 2017. Repairing inconsistent answer set programs using rules of thumb: a gene regulatory networks case study. International Journal of Approximate Reasoning 83 , pp.243-264. (10.1016/j.ijar.2017.01.012)
• Merhej, E. et al., 2017. Recommending treatments for comorbid patients using word-based and phrase-based alignment methods. Presented at: The 29th Benelux Conference on Artificial Intelligence Groningen 8-9 November 2017.
• Shi, B. et al., 2017. Jointly learning word embeddings and latent topics. Presented at: 40th International ACM SIGIR Conference on Research and Development in Information Retrieval Tokyo, Japan 7-11 August 2017. SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM. , pp.375-384. (10.1145/3077136.3080806)
• Sourek, G. et al., 2017. Learning predictive categories using lifted relational neural networks. Presented at: ILP 2016: International Conference on Inductive Logic Programming London, UK 4-6 September 2016. Published in: Cussens, J. and Russo, A. eds. Inductive Logic Programming. Vol. 10326.Lecture Notes in Computer Science Cham: Springer. , pp.108-119. (10.1007/978-3-319-63342-8_9)
• Svatos, M. et al., 2017. Pruning hypothesis spaces using learned domain theories. Presented at: International Conference on Inductive Logic Programming Orléans, France 4-6 September 2017.

2016

• Ager, T. , Kuzelka, O. and Schockaert, S. 2016. Inducing symbolic rules from entity embeddings using auto-encoders. Presented at: Eleventh International Workshop on Neural-Symbolic Learning and Reasoning New York; NY, 16-17 July 2016
• De Clercq, S. et al., 2016. Solving stable matching problems using answer set programming. Theory and Practice of Logic Programming 16 (3), pp.247-268. (10.1017/S147106841600003X)
• De Clercq, S. et al., 2016. Formalizing commitment-based deals in Boolean Games. Presented at: 22nd European Conference on Artificial Intelligence The Hague 29 August - 2 September 2016.
• Jameel, S. et al., 2016. Exploring urban lifestyles using a nonparametric temporal graphical model. Presented at: ACM International Conference on the Theory of Information Retrieval Newark, DE, USA 13-16 September 2016.
• Jameel, S. and Schockaert, S. 2016. D-GloVe: A feasible least squares model for estimating word embedding densities. Presented at: 26th International Conference on Computational Linguistics Osaka, Japan 11-16 December 2016.
• Jameel, S. and Schockaert, S. 2016. Entity embeddings with conceptual subspaces as a basis for plausible reasoning. Presented at: 22nd European Conference on Artificial Intelligence The Hague, The Netherlands 29 August - 2 September 2016.
• Kuzelka, O. , Davis, J. and Schockaert, S. 2016. Constructing Markov logic networks from first-order default rules. Presented at: 25th International Conference on Inductive Logic Programming Kyoto, Japan 20-22 August 2016.
• Kuzelka, O. , Davis, J. and Schockaert, S. 2016. Interpretable encoding of densities using possibilistic logic. Presented at: 22nd European Conference on Artificial Intelligence The Hague 29 August - 2 September 2016.
• Kuzelka, O. , Davis, J. and Schockaert, S. 2016. Learning possibilistic logic theories from default rules. Presented at: 25th International Joint Conference on Artificial Intelligence New York, NY, USA 9-15 July 2016.
• Kuzelka, O. , Davis, J. and Schockaert, S. 2016. Stratified knowledge bases as interpretable probabilistic models. Presented at: Interpretable ML for Complex Systems NIPS 2016 Workshop Barcelona, Spain 9 December 2016.
• Liao, Y. et al., 2016. Who wants to join me? Companion recommendation in location based social networks. Presented at: ACM International Conference on the Theory of Information Retrieval Newark, DE 12 - 16 September 2016. Published in: Carterette, B. et al., ICTIR '16 Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval. New York, NY: ACM. , pp.271-280. (10.1145/2970398.2970420)
• Long, Z. et al., 2016. Indexing large geographic datasets with compact qualitative representation. International Journal of Geographical Information Science 30 (6), pp.1072-1094.
• Long, Z. , Schockaert, S. and Li, S. 2016. Encoding large RCC8 scenarios using rectangular pseudo-solutions. Presented at: 15th International Conference on Principles of Knowledge Representation and Reasoning Cape Town, South Africa 25-29 April 2015.
• Merhej, E. et al., 2016. Generating conflict-free treatments for patients with comorbidity using ASP. Presented at: International Joint Workshop KR4HC 2016 - ProHealth 2016 Munich, Germany 2 September 2016.
• Mushthofa, M. , Schockaert, S. and Cock, M. D. 2016. Computing attractors of multi-valued gene regulatory networks using fuzzy answer set programming. Presented at: IEEE World Congress on Computational Intelligence Vancouver, BC, Canada 24-29 July 2016.
• Schockaert, S. and Jameel, S. 2016. Plausible reasoning based on qualitative entity embeddings. Presented at: 25th International Joint Conference on Artificial Intelligence New York, USA 9-15 July 2016.
• Van Canneyt, S. , Schockaert, S. and Dhoedt, B. 2016. Categorizing events using spatio-temporal and user features from Flickr. Information Sciences 328 , pp.76-96. (10.1016/j.ins.2015.08.032)

2015

• Bauters, K. et al., 2015. Characterizing and extending answer set semantics using possibility theory. Theory and Practice of Logic Programming 15 , pp.79-116. (10.1017/S147106841300063X)
• Blondeel, M. et al., 2015. On the relationship between fuzzy autoepistemic logic and fuzzy modal logics of belief. Fuzzy Sets and Systems 276 , pp.74-99. (10.1016/j.fss.2015.02.018)
• De Clercq, S. et al., 2015. Multilateral negotiation in Boolean games with incomplete information using generalized possibilistic logic. Presented at: International Joint Conference on Artificial Intelligence Buenos Aires, Argentina 25 31 July 2015.
• Derrac, J. and Schockaert, S. 2015. Inducing semantic relations from conceptual spaces: a data-driven approach to plausible reasoning. Artificial Intelligence 228 , pp.66-94. (10.1016/j.artint.2015.07.002)
• Dubois, D. , Prade, H. and Schockaert, S. 2015. Extending answer set programming using generalized possibilistic logic. Presented at: International Workshop on Ontologies and Logic Programming for Query Answering Buenos Aires, Argentina 25 July 2015.
• Jameel, S. et al., 2015. A unified posterior regularized topic model with maximum margin for learning-to-rank. Presented at: CIKM 2015: Conference on Information and Knowledge Management Melbourne, Australia 19-23 October 2015. CIKM '15 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management. ACM. , pp.103-112. (10.1145/2806416.2806482)
• Kuzelka, O. , Davis, J. and Schockaert, S. 2015. Encoding Markov logic networks in possibilistic logic. Presented at: 31st Conference on Uncertainty in Artificial Intelligence Amsterdam 12-16 July 2015.
• Merhej, E. , Schockaert, S. and De Cock, M. 2015. Using rules of thumb for repairing inconsistent answer set programs. Presented at: SUM 2015: International Conference on Scalable Uncertainty Management Quebec City, QC, Canada 16-18 September 2015. Published in: Beierle, C. and Dekhtyar, A. eds. Scalable Uncertainty Management: 9th International Conference, SUM 2015, Québec City, QC, Canada, September 16-18, 2015. Proceedings. Vol. 9310.Springer Verlag. , pp.368-381. (10.1007/978-3-319-23540-0_25)
• Mushthofa, M. , Schockaert, S. and De Cock, M. 2015. Solving disjunctive fuzzy answer set programs. Presented at: LPNMR 2015: International Conference on Logic Programming and Nonmonotonic Reasoning Lexington, KY, USA 27-30 September 2015. Published in: Calimeri, F. , Ianni, G. and Truszczynski, M. eds. Logic Programming and Nonmonotonic Reasoning: 13th International Conference, LPNMR 2015, Lexington, KY, USA, September 27-30, 2015. Proceedings. Vol. 9345.Lecture Notes in Computer Science Springer. , pp.453-466. (10.1007/978-3-319-23264-5_38)
• Schockaert, S. 2015. Lexical inference as a spatial reasoning problem. Presented at: International Workshop on Spatio-Temporal Dynamics Buenos Aires, Argentina 26 July 2015.
• Schockaert, S. and Derrac, J. 2015. Commonsense reasoning based on betweenness and direction in distributional models. Presented at: AAAI Spring Symposium on Knowledge Representation and Reasoning:Integrating Symbolic and Neural Approaches Stanford University 23 -25 March 2015.
• Schockaert, S. and Lee, J. H. 2015. Qualitative reasoning about directions in semantic spaces. Presented at: International Joint Conference on Artificial Intelligence Buenos Aires, Argentina 25 - 31 July 2015.
• Schockaert, S. and Li, S. 2015. Realizing RCC8 networks using convex regions. Artificial Intelligence 218 , pp.74-105. (10.1016/j.artint.2014.10.002)

2014

• Bauters, K. et al., 2014. Semantics for possibilistic answer set programs: Uncertain rules versus rules with uncertain conclusions. International Journal of Approximate Reasoning 55 (2), pp.739-761. (10.1016/j.ijar.2013.09.006)
• Blondeel, M. et al., 2014. Fuzzy autoepistemic logic and its relation to fuzzy answer set programming. Fuzzy Sets and Systems 239 , pp.51-80. (10.1016/j.fss.2012.09.012)
• Blondeel, M. et al., 2014. Complexity of fuzzy answer set programming under Lukasiewicz semantics. International Journal of Approximate Reasoning 55 (9), pp.1971-2003. (10.1016/j.ijar.2013.10.011)
• De Clercq, S. et al., 2014. Decentralized computation of pareto optimal pure nash equilibria of boolean games with privacy concerns. Presented at: International Conference on Agents and Artificial Intelligence (ICAART 2014) Angers, France 6-8 March 2014. Published in: Duval, B. et al., Issue Proceedings ICAART 2014. Vol. 2., pp.50-59. (10.5220/0004811700500059)
• De Clercq, S. et al., 2014. Using answer set programming for solving boolean games. Presented at: 14th International conference on Principles of Knowledge Representation and Reasoning (KR-2014) Vienna, Austria 20-24 July 2014. Published in: Baral, C. , De Giacomo, G. and Eiter, T. eds. Principles of Knowledge Representation and Reasoning, 14th International conference, Proceedings.. AAAI. , pp.602-605.
• De Clercq, S. et al., 2014. Possibilistic Boolean games: strategic reasoning under incomplete information. Presented at: JELIA 2014: 14th European Conference on Logics in Artificial Intelligence Funchal, Madeira, Portugal 24-26 September 2014. Published in: Fermé, E. and Leite, J. eds. Logics in Artificial Intelligence: 14th European Conference, JELIA 2014, Funchal, Madeira, Portugal, September 24-26, 2014. Proceedings. Vol. 8761.Lecture Notes in Computer Science Springer. , pp.196-209. (10.1007/978-3-319-11558-0_14)
• Derrac, J. and Schockaert, S. 2014. Characterising semantic relatedness using interpretable directions in conceptual spaces. Presented at: 2nd European Conference on Artificial Intelligence (ECAI) Prague, Czech Republic 18-22 August 2014. Published in: Schaub, T. , Friedrich, G. and O'Sullivan, B. eds. ECAI 2014: 21st European Conference on Artificial Intelligence. Vol. 263.Frontiers in Artificial Intelligence and Applications Amsterdam: IOS Press. , pp.243-248. (10.3233/978-1-61499-419-0-243)
• Derrac, J. and Schockaert, S. 2014. Enriching taxonomies of place types using Flickr. Presented at: FoIKS 2014: 8th International Symposium on Foundations of Information and Knowledge Systems Bordeaux, France 3-7 March 2014. Published in: Beierle, C. and Meghini, C. eds. Foundations of Information and Knowledge Systems: 8th International Symposium, FoIKS 2014, Bordeaux, France, March 3-7, 2014. Proceedings. Vol. 8367.Lecture Notes in Computer Science Springer Verlag. , pp.174-192. (10.1007/978-3-319-04939-7_8)
• Dubois, D. , Prade, H. and Schockaert, S. 2014. Reasoning about uncertainty and explicit ignorance in generalized possibilistic logic. Presented at: 2nd European Conference on Artificial Intelligence (ECAI) Prague, Czech Republic 18-22 August 2014. Published in: Schaub, T. , Friedrich, G. and O'Sullivan, B. eds. ECAI 2014: 21st European Conference on Artificial Intelligence. Vol. 263.Frontiers in Artificial Intelligence and Applications Amsterdam: IOS Press. , pp.261-266. (10.3233/978-1-61499-419-0-261)
• Dubois, D. , Prade, H. and Schockaert, S. 2014. Stable models in generalized possibilistic logic. Presented at: 13th International Conference on Principles of Knowledge Representation and Reasoning Rome, Italy 10-14 June 2012. Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning. AAAI Press.
• Mushthofa, M. , Schockaert, S. and De Cock, M. 2014. A finite-valued solver for disjunctive fuzzy answer set programs. Presented at: ECAI Prague, Czech Republic 18-22 August 2014. Published in: Schaub, T. , Friedrich, G. and O'Sullivan, B. eds. ECAI 2014: Frontiers in Artificial Intelligence and Applications. Vol. 263.IOP Publishing. , pp.645-650. (10.3233/978-1-61499-419-0-645)
• Schockaert, S. and Li, S. 2014. Convex solutions of RCC8 networks. Presented at: 20th European Conference on Artificial Intelligence (ECAI 2012) Montpellier, France 27-31 August 2012. Published in: De Raedt, L. et al., Ecai 2012: 20th European Conference on Artificial Intelligence. Frontiers in Artificial Intelligence and Applications Vol. 242. IOS Press. , pp.726-731. (10.3233/978-1-61499-098-7-726)
• Schockaert, S. and Prade, H. 2014. Completing symbolic rule bases using betweenness and analogical proportion. Studies in Computational Intelligence 548 , pp.195-215. (10.1007/978-3-642-54516-0_8)
• Van Laere, O. et al., 2014. Spatially aware term selection for geotagging. IEEE Transactions on Knowledge and Data Engineering 26 (1), pp.221-234. (10.1109/TKDE.2013.42)
• Van Laere, O. et al., 2014. Georeferencing Wikipedia documents using data from social media sources. ACM Transactions on Information Systems 32 (3) 12. (10.1145/2629685)

2013

• Bauters, K. et al., 2013. Expressiveness of communication in answer set programming. Theory and Practice of Logic Programming 13 (3), pp.361-394. (10.1017/S1471068411000561)
• Blondeel, M. et al., 2013. Towards a deeper understanding of nonmonotonic reasoning with degrees. Presented at: 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013) Beijing, China 3-9 August 2013. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Palo Alto, California: AAAI. , pp.3205-3206.
• De Clercq, S. et al., 2013. Modeling stable matching problems with answer set programming. Presented at: 7th International Symposium, RuleML 2013 Seattle, USA 11-13 July 2013. Published in: Morgenstern, L. et al., Theory, Practice, and Applications of Rules on the Web: 7th International Symposium, RuleML 2013, Seattle, WA, USA, July 11-13, 2013. Proceedings. Vol. 8035.Lecture Notes in Computer Science Berlin: Springer. , pp.68-83. (10.1007/978-3-642-39617-5_10)
• Martin, G. H. et al., 2013. An exploratory study on content-based filtering of call for papers. Presented at: IRFC 2013: 6th Information Retrieval Facility Conference Limassol, Cyprus 7-9 October 2013. Published in: Lupu, M. , Kanoulas, E. and Loizides, F. eds. Multidisciplinary Information Retrieval: 6th Information Retrieval Facility Conference, IRFC 2013, Limassol, Cyprus, October 7-9, 2013. Proceedings. Vol. 8201.Lecture Notes in Computer Science Berlin and Heidelberg: Springer. , pp.58-69. (10.1007/978-3-642-41057-4_7)
• Martin, G. H. et al., 2013. Using semi-structured data for assessing research paper similarity. Information Sciences 221 , pp.245-261. (10.1016/j.ins.2012.09.044)
• Schockaert, S. and Li, S. 2013. Combining RCC5 relations with betweenness information. Presented at: 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013) Beijing, China 3-9 August 2013. Published in: Rossi, F. and International Joint Conferences on Artificial Intelligence, .. eds. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Palo Alto, California: AAAI. , pp.1083-1089.
• Schockaert, S. and Prade, H. 2013. Interpolative and extrapolative reasoning in propositional theories using qualitative knowledge about conceptual spaces. Artificial Intelligence 202 , pp.86-131. (10.1016/j.artint.2013.07.001)
• Schockaert, S. and Prade, H. 2013. Interpolative reasoning with default rules. Presented at: 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013) Beijing, China 3-9 August 2013. Proceedings of The Twenty-Third International Joint Conference on Artificial Intelligence. Palo Alto, California: AAAI. , pp.1090-1096.
• Van Canneyt, S. , Schockaert, S. and Dhoedt, B. 2013. Discovering and characterizing places of interest using Flickr and Twitter. International Journal on Semantic Web and Information Systems 9 (3), pp.77-104. (10.4018/ijswis.2013070105)
• Van Laere, O. , Schockaert, S. and Dhoedt, B. 2013. Georeferencing Flickr resources based on textual meta-data. Information Sciences 238 , pp.52-74. (10.1016/j.ins.2013.02.045)

2012

• Bauters, K. et al., 2012. Possible and necessary answer sets of possibilistic answer set programs. 2012 IEEE 24TH International Conference on Tools with Artificial Intelligence (ICTAI 2012), vol. 1 , pp.836-843. (10.1109/ICTAI.2012.117)
• Dubois, D. , Prade, H. and Schockaert, S. 2012. Règles et méta-règles en théorie des possibilités: De la logique possibiliste à la programmation par ensembles-réponses. Revue d'Intelligence Artificielle 26 , pp.63-83.
• Janssen, J. et al., 2012. A core language for fuzzy answer set programming. International Journal of Approximate Reasoning 53 (4), pp.660-692. (10.1016/j.ijar.2012.01.005)
• Janssen, J. et al., 2012. Reducing fuzzy answer set programming to model finding in fuzzy logics. Theory and Practice of Logic Programming 12 (6), pp.811-842. (10.1017/S1471068411000093)
• Schockaert, S. , Janssen, J. and Vermeir, D. 2012. Fuzzy equilibrium logic. ACM Transactions on Computational Logic 13 (4) 33. (10.1145/2362355.2362361)
• Schockaert, S. , Janssen, J. and Vermeir, D. 2012. Fuzzy equilibrium logic: declarative problem solving in continuous domains. ACM Transactions on Computational Logic 13 (4) 33.
• Schockaert, S. , Janssen, J. and Vermeir, D. 2012. Satisfiability checking in Łukasiewicz logic as finite constraint satisfaction. Journal of Automated Reasoning 49 (4), pp.493-550. (10.1007/s10817-011-9227-0)
• Van Canneyt, S. et al., 2012. Detecting places of interest using social media. Presented at: 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT) Macau, China 4-7 December 2012. Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on. Vol. 1.IEEE. , pp.447-451. (10.1109/WI-IAT.2012.19)
• Van Canneyt, S. et al., 2012. Using social media to find places of interest. Presented at: 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2012) Redondo Beach, CA, USA 6-9 November 2012. GEOCROWD '12 Proceedings of the 1st ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information. New York: ACM. , pp.2-8. (10.1145/2442952.2442954)
• Van Laere, O. , Schockaert, S. and Dhoedt, B. 2012. Georeferencing Flickr photos using language models at different levels of granularity: An evidence based approach. Journal of Web Semantics 16 , pp.17-31. (10.1016/j.websem.2012.05.005)

2011

• Bauters, K. et al., 2011. Weak and strong disjunction in possibilistic ASP. Presented at: SUM 2011: 5th International Conference on Scalable Uncertainty Management Dayton, OH, USA 10-13 October 2011. Published in: Benferhat, S. and Grant, J. eds. Scalable Uncertainty Management: 5th International Conference, SUM 2011, Dayton, OH, USA, October 10-13, 2011. Proceedings. Vol. 6929.Lecture Notes in Computer Science Berlin and Heidelberg: Springer. , pp.475-488. (10.1007/978-3-642-23963-2_37)
• Bauters, K. et al., 2011. Communicating ASP and the polynomial hierarchy. Presented at: LPNMR 2011: 11th International Conference on Logic Programming and Nonmonotonic Reasoning Vancouver, BC, Canada 16-19 May 2011. Published in: Delgrande, J. P. and Faber, W. eds. Logic Programming and Nonmonotonic Reasoning: 11th International Conference, LPNMR 2011, Vancouver, Canada, May 16-19, 2011. Proceedings. Vol. 6645.Lecture Notes in Computer Science Berlin and Heidelberg: Springer. , pp.67-79. (10.1007/978-3-642-20895-9_8)
• Dubois, D. , Prade, H. and Schockaert, S. 2011. Rules and meta-rules in the framework of possibility theory and possibilistic logic. Scientia Iranica 18 (3), pp.566-573. (10.1016/j.scient.2011.04.008)
• Janssen, J. et al., 2011. Aggregated fuzzy answer set programming. Annals of Mathematics and Artificial Intelligence 63 (2), pp.103-147. (10.1007/s10472-011-9256-8)
• Prade, H. and Schockaert, S. 2011. Completing rule bases in symbolic domains by analogy making. Presented at: EUSFLAT-2011 Aix-Les-Bains, France 18-22 July 2011. Published in: Galichet, S. , Montero, J. and Mauris, G. eds. Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011) and LFA-2011. Vol. 1.Atlantis Press. , pp.928-934. (doi:10.2991/eusflat.2011.76)
• Schockaert, S. 2011. Vague regions in geographic information retrieval. SIGSPATIAL Special 3 (2), pp.24-28. (10.1145/2047296.2047302)
• Schockaert, S. and Prade, H. 2011. Qualitative reasoning about incomplete categorization rules based on interpolation and extrapolation in conceptual spaces. Lecture Notes in Computer Science 6929 , pp.303-316. (10.1007/978-3-642-23963-2_24)
• Schockaert, S. and Prade, H. 2011. Solving conflicts in information merging by a flexible interpretation of atomic propositions. Artificial Intelligence 175 (11), pp.1815-1855. (10.1016/j.artint.2011.04.001)
• Schockaert, S. , Smart, P. D. and Twaroch, F. 2011. Generating approximate region boundaries from heterogeneous spatial information: an evolutionary approach. Information Sciences 181 (2), pp.257-283. (10.1016/j.ins.2010.09.021)

2010

• Martin, G. H. et al., 2010. Metadata impact on research paper similarity. Presented at: 14th ECDL Conference Glasgow, Scotland 6-10 September 2010. Published in: Lalmas, M. et al., Research and Advanced Technology for Digital Libraries : 14th European Conference, ECDL 2010, Glasgow, UK, September 6-10, 2010, proceedings. Lecture Notes in Computer Science Vol. 6273. Berlin-Heidelberg: Springer-Verlag. , pp.457-460. (10.1007/978-3-642-15464-5_56)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2010. Reasoning about fuzzy temporal information from the web: towards retrieval of historical events. Soft Computing 14 (8), pp.869-886. (10.1007/s00500-009-0471-8)
• Van Laere, O. , Schockaert, S. and Dhoedt, B. 2010. Combining multi-resolution evidence for georeferencing Flickr images. Lecture Notes in Computer Science 6379 , pp.347-360. (10.1007/978-3-642-15951-0_32)

2009

• Janssen, J. et al., 2009. Fuzzy answer set programming with literal preferences. Presented at: 2009 International Fuzzy Systems Association World Congress Lisbon, Portugal 20-24 July 2009. Published in: Carvalho, J. P. et al., Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference, Lisbon, Portugal, July 20-24, 2009.. European Society for Fuzzy Logic and Technology. , pp.1347-1352.
• Janssen, J. et al., 2009. General fuzzy answer set programs. Lecture Notes in Computer Science 5571 , pp.352-359. (10.1007/978-3-642-02282-1_44)
• Schockaert, S. and De Cock, M. 2009. Efficient algorithms for fuzzy qualitative temporal reasoning. IEEE Transactions on Fuzzy Systems 17 (4), pp.794-808. (10.1109/TFUZZ.2008.924333)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2009. Spatial reasoning in a fuzzy region connection calculus. Artificial Intelligence 173 (2), pp.258-298. (10.1016/j.artint.2008.10.009)
• Schockaert, S. et al. 2009. Finite satisfiability in infinite-valued Lukasiewicz logic. Lecture Notes in Computer Science (5785), pp.240-254. (10.1007/978-3-642-04388-8_19)
• Schockaert, S. et al. 2009. Answer sets in a fuzzy equilibrium logic. Lecture Notes in Computer Science (5837), pp.135-149. (10.1007/978-3-642-05082-4_10)
• Schockaert, S. and Prade, H. 2009. Merging conflicting propositional knowledge by similarity. Presented at: 21st IEEE International Conference on Tools with Artificial Intelligence Newark, NJ, USA 2-5 November 2009. ICTAI: 2009 21st International Conference on Tools with Artificial Intelligence, proceedings. IEEE. , pp.224-228. (10.1109/ICTAI.2009.56)

2008

• Schockaert, S. et al. 2008. Fuzzy region connection calculus: an interpretation based on closeness. International Journal of Approximate Reasoning 48 (1), pp.332-347. (10.1016/j.ijar.2007.10.002)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2008. Fuzzifying Allen's temporal interval relations. IEEE Transactions on Fuzzy Systems 16 (2), pp.517-533. (10.1109/TFUZZ.2007.895960)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2008. Location approximation for local search services using natural language hints. International Journal of Geographical Information Science 22 (3), pp.315-336.
• Schockaert, S. and De Cock, M. 2008. Temporal reasoning about fuzzy intervals. Artificial Intelligence 172 (8-9), pp.1158-1193. (10.1016/j.artint.2008.01.001)
• Schockaert, S. et al. 2008. Fuzzy region connection calculus: representing vague topological information. International Journal of Approximate Reasoning 48 (1), pp.314-331. (10.1016/j.ijar.2007.10.001)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2008. Modelling nearness and cardinal directions between fuzzy regions. Presented at: IEEE International Conference on Fuzzy Systems Hong Kong, China 1-6 June 2008. 2008 IEEE International Conference on Fuzzy Systems : Hong Kong, China, 1-6 June 2008. Piscataway, NJ: IEEE. , pp.1548-1555. (10.1109/FUZZY.2008.4630578)
• Schockaert, S. et al. 2008. Mining topological relations from the Web. Presented at: 28th International Workshop on Database and Expert Systems Applications Turin, Italy 1-5 September 2008. Published in: Tjoa, A. M. and Wagner, R. R. eds. DEXA 2008: 19th International Conference on Database and Expert Systems Applications : proceedings, 1-5 September, 2008, Turin, Italy. Los Alamitos, CA: IEEE Computer Society,. , pp.652-656. (10.1109/DEXA.2008.15)

2007

• Schockaert, S. et al. 2007. Clustering web search results using fuzzy ants. International Journal of Intelligent Systems 22 (5), pp.455-474. (10.1002/int.20209)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2007. Qualitative temporal reasoning about vague events. Presented at: Twentieth International Joint Conference on Artificial Intelligence (IJCAI) Hyderbad, India 6-12 January 2007. Published in: Veloso, M. M. ed. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI): Hyderbad, India, 6-12 January, 2007. AAAI Press. , pp.569-574.

2006

• Schockaert, S. et al. 2006. Question answering with imperfect temporal information. Presented at: 7th International Conference on Flexible Query Answering Systems (FQAS 2006) Milan, Italy 7-10 June 2006. Published in: Larsen, H. L. et al., Flexible query answering systems: 7th international conference, FQAS 2006, Milan, Italy, June 7-10, 2006. Lecture Notes in Artificial Intelligence Vol. 4027. Berlin Heidelberg: Springer-Verlag. , pp.647-658. (10.1007/11766254)
• Schockaert, S. et al. 2006. Fuzzy spatial relations between vague regions. Presented at: 3rd International IEEE Conference on Intelligent Systems London, UK September 2006. Proceedings of the Third IEEE Conference on Intelligent Systems 2006. IEEE. , pp.217-222. (10.1109/IS.2006.348421)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2006. An efficient characterization of fuzzy temporal interval relations. Presented at: 2006 IEEE International Conference on Fuzzy Systems Vancouver, CanadaProceedings of the IEEE World Congress on Computational Intelligence (FUZZ-IEEE). IEEE. , pp.1894-1901. (10.1109/FUZZY.2006.1681963)
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2006. Imprecise temporal interval relations. Presented at: 6th International Workshop on Fuzzy Logic and Applications Crema, Italy 15-17 September 2005. Published in: Bloch, I. , Petrosino, A. and Tettamanzi, A. G. B. eds. Fuzzy logic and applications: 6th international workshop, WILF 2005, Crema, Italy, September 15-17, 2005, revised selected papers. Lecture Notes in Artificial Intelligence Vol. 3849. Springer. , pp.108-113.

2005

• Schockaert, S. , De Cock, M. and Cornelis, C. 2005. Relatedness of fuzzy sets. Journal of Intelligent and Fuzzy Systems 16 (4), pp.297-303.
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2005. Automatic acquisition of fuzzy footprints. Presented at: OTM 2005 Agia Napa, Cyprus October 31 - November 4 2005. Published in: Tari, Z. ed. On the Move to Meaningful Internet Systems 2005: OTM 2005 Workshops. Lecture Notes in Computer Science Vol. 3762. Springer. , pp.1077-1086.
• Schockaert, S. , De Cock, M. and Kerre, E. E. 2005. Fuzzy constraint based answer validation. Presented at: Third International Atlantic Web Intelligence Conference (AWIC 2005) Lodz, Poland 6-9 June 2005. Published in: Szczepaniak, P. S. , Kacprzyk, J. and Niewiadomski, A. eds. Advances in Web Intelligence: proceedings of Third International Atlantic Web Intelligence Conference, AWIC 2005, Lodz, Poland, June 6-9, 2005.. Lecture Notes in Computer Science Vol. 3528. Berlin Heidelberg: Springer Verlag. , pp.394-400. (10.1007/b137066)

2004

• Schockaert, S. et al. 2004. Efficient clustering with fuzzy ants. Presented at: 6th International FLINS Conference Blankenberge, Belgium 1-2 September 2004. Published in: Ruan, D. et al., Applied computational intelligence: proceedings of the 6th international FLINS conference. World Scientific Publishing. , pp.195-200.
• Schockaert, S. et al. 2004. Fuzzy ant based clustering. Presented at: 4th International Workshop on Ant Colony Optimization and Swarm Intelligence (ANTS 2004) Brussels, Belgium 5-8 September 2004. Published in: Dorigo, M. et al., Ant colony optimization and swarm intelligence: 4th international workshop, ANTS 2004, Brussels, Belgium, September 5-8, 2004, proceedings. Lecture Notes in Computer Science Vol. 3172. Springer. , pp.342-349.