Improving Difficult Queries by Leveraging Clusters in Term Graph-Reference-Cited by-同舟云学术

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Improving Difficult Queries by Leveraging Clusters in Term Graph

Published:2015 Issue: Volume: Page:426-432
ISSN:0302-9743
Container-title:Information Retrieval Technology
language:
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Author:

Anand Rajul,Kotov Alexander

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-28940-3_37

Reference11 articles.

1. Bai, J., Song, D., Bruza, P., Nie, J.-Y., Cao, G.: Query expansion using term relationships in language models for information retrieval. In: Proceedings of CIKM 2005, pp. 688–695 (2005)

2. Karimzadehgan, M., Zhai, C.: Estimation of statistical translation models based on mutual information for ad hoc information retrieval. In: Proceedings of SIGIR 2010, pp. 323–330 (2010)

3. Kotov, A., Zhai, C.: Interactive sense feedback for difficult queries. In: Proceedings of CIKM 2011, pp. 59–66 (2009)

4. Kotov, A., Zhai, C.: Tapping into knowledge base for concept feedback: leveraging conceptnet to improve search results for difficult queries. In: Proceedings of WSDM 2012, pp. 403–412 (2012)

5. Kurland, O.: The opposite of smoothing: a language model approach to ranking query-specific document clusters. In: Proceedings of SIGIR 2008, pp. 171–178 (2008)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sequential Query Expansion using Concept Graph;Proceedings of the 25th ACM International on Conference on Information and Knowledge Management;2016-10-24

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