DeepQFM: a deep learning based query facets mining method-Reference-Cited by-同舟云学术

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DeepQFM: a deep learning based query facets mining method

Published:2023-10-30 Issue:1-2 Volume:26 Page:
ISSN:1386-4564
Container-title:Information Retrieval Journal
language:en
Short-container-title:Inf Retrieval J

Author:

Deng Zhirui,Dou Zhicheng,Wen Ji-Rong

Funder

National Natural Science Foundation of China

Beijing Outstanding Young Scientist Program

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s10791-023-09427-0.pdf

Reference53 articles.

1. Aliannejadi, M., Zamani, H., Crestani, F., & Croft, W. B. (2019). Asking clarifying questions in open-domain information-seeking conversations. In Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval (pp. 475–484).

2. Anick, P. (2003). Using terminological feedback for web search refinement: A log-based study. In Proceedings of the 26th annual international ACM SIGIR conference on research and development in information retrieval (pp. 88–95).

3. Baeza-Yates, R., Hurtado, C., & Mendoza, M. (2004). Query recommendation using query logs in search engines. International conference on extending database technology (pp. 588–596).

4. Basu Roy, S.,Wang, H., Das, G., Nambiar, U., & Mohania, M. (2008). Minimumeffort driven dynamic faceted search in structured databases. In Proceedings of the 17th ACM conference on information and knowledge management (pp. 13–22).

5. Ben-Yitzhak, O., Golbandi, N., Har’El, N., Lempel, R., Neumann, A., Ofek-Koifman, S., Sheinwald, D., Shekita, E., Sznajder, B., & Yogev, S. (2008). Beyond basic faceted search. In Proceedings of the 2008 international conference on web search and data mining (pp. 33–44).

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