ECIR 23 Tutorial: Neuro-Symbolic Approaches for Information Retrieval-Reference-Cited by-同舟云学术

ECIR 23 Tutorial: Neuro-Symbolic Approaches for Information Retrieval

Published:2023 Issue: Volume: Page:324-330
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Dietz Laura^ORCID,Bast Hannah^ORCID,Chatterjee Shubham^ORCID,Dalton Jeff^ORCID,Meij Edgar^ORCID,de Vries Arjen^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-28241-6_33

Reference25 articles.

1. Bast, H., Haussmann, E.: More accurate question answering on freebase. In: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 1431–1440 (2015)

2. Cao, N.D., Izacard, G., Riedel, S., Petroni, F.: Autoregressive entity retrieval. CoRR abs/2010.00904 (2020). https://arxiv.org/abs/2010.00904

3. Chatterjee, S., Dietz, L.: BERT-ER: query-specific BERT entity representations for entity ranking. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022, pp. 1466–1477. Association for Computing Machinery, New York (2022). https://doi.org/10.1145/3477495.3531944

4. Chatterjee, S., Dietz, L.: Predicting guiding entities for entity aspect linking. In: Proceedings of the 31st ACM International Conference on Information and Knowledge Management, CIKM 2022. Association for Computing Machinery, New York (2022). https://doi.org/10.1145/3511808.3557671

5. Chen, X., Hu, Z., Sun, Y.: Fuzzy logic based logical query answering on knowledge graphs. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, pp. 3939–3948 (2022)

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