Keyword Embeddings for Query Suggestion

Author:

Gabín JorgeORCID,Ares M. EduardoORCID,Parapar JavierORCID

Publisher

Springer Nature Switzerland

Reference26 articles.

1. André, P.A., Schraefel, M.C., Teevan, J., Dumais, S.T.: Discovery is never by chance: designing for (un)serendipity. In: Bryan-Kinns, N., Gross, M.D., Johnson, H., Ox, J., Wakkary, R. (eds.) Proceedings of the 7th Conference on Creativity & Cognition, Berkeley, California, USA, 26–30 October 2009, pp. 305–314. ACM (2009). doi: https://doi.org/10.1145/1640233.1640279

2. Beltagy, I., Lo, K., Cohan, A.: SciBERT: a pretrained language model for scientific text. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 3615–3620. Association for Computational Linguistics, Hong Kong, China (2019). https://doi.org/10.18653/v1/D19-1371

3. Bennani-Smires, K., Musat, C., Hossmann, A., Baeriswyl, M., Jaggi, M.: Simple unsupervised keyphrase extraction using sentence embeddings. In: Korhonen, A., Titov, I. (eds.) Proceedings of the 22nd Conference on Computational Natural Language Learning, CoNLL 2018, Brussels, Belgium, 31 Oct - 1 Nov 2018, pp. 221–229. Association for Computational Linguistics (2018). https://doi.org/10.18653/v1/k18-1022

4. Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. Assoc. Comput. Linguist. 5, 135–146 (2017)

5. Buchanan, S.A., Sauer, S., Quan-Haase, A., Agarwal, N.K., Erdelez, S.: Amplifying chance for positive action and serendipity by design. Proceed. Assoc. Inf. Sci. Technol. 57(1), e288 (2020)

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