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Query performance prediction for information retrieval based on covering topic score

Lang, Hao and Wang, Bin and Jones, Gareth J.F. and Li, Jintao and Ding, Fan and Liu, Yi-Xuan (2008) Query performance prediction for information retrieval based on covering topic score. Journal of Computer Science and Technology, 23 (4). pp. 590-601. ISSN 1860-4749

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We present a statistical method called Covering Topic Score (CTS) to predict query performance for information retrieval. Estimation is based on how well the topic of a user's query is covered by documents retrieved from a certain retrieval system. Our approach is conceptually simple and intuitive, and can be easily extended to incorporate features beyond bag-of-words such as phrases and proximity of terms. Experiments demonstrate that CTS significantly correlates with query performance in a variety of TREC test collections, and in particular CTS gains more prediction power benefiting from features of phrases and proximity of terms. We compare CTS with previous state-of-the-art methods for query performance prediction including clarity score and robustness score. Our experimental results show that CTS consistently performs better than, or at least as well as, these other methods. In addition to its high effectiveness, CTS is also shown to have very low computational complexity, meaning that it can be practical for real applications.

Item Type:Article (Published)
Uncontrolled Keywords:information storage and retrieval; information search and retrieval; query performance prediction; covering topic score
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
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Copyright Information:© 2008 Springer-Verlag. The original publication is available at
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:16507
Deposited On:24 Aug 2011 11:31 by Shane Harper. Last Modified 02 Nov 2016 15:59

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