Mining specific and general features in both positive and negative relevance feedback

Li, Yuefeng and Tao, Xiaohui and Algarni, Abdulmohsen and Wu, Sheng-Tang (2009) Mining specific and general features in both positive and negative relevance feedback. In: TREC 2009: 18th Text REtrieval Conference, 17-20 Nov 2009, Gaithersburg, MD. United States.

Abstract

User relevance feedback is usually utilized by Web systems to interpret user information needs and retrieval effective results for users. However, how to discover useful knowledge in user relevance feedback and how to wisely
use the discovery knowledge are two critical problems. In TREC 2009, we participated in the Relevance Feedback Track and proposed a model consisting of two innovative stages: one for subject-based query expansion for obtaining
pseudo-relevance feedback; one for relevance feature discovery to find useful patterns and terms in relevance feedback for ranking documents. In this document, the detailed descriptions are given, as well as the related discussions.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: No
Item Status: Live Archive
Additional Information: Paper no. 36.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 25 Aug 2016 04:44
Last Modified: 25 Aug 2016 04:44
Uncontrolled Keywords: web searching; techniques; relevance
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0807 Library and Information Studies > 080703 Human Information Behaviour
08 Information and Computing Sciences > 0807 Library and Information Studies > 080704 Information Retrieval and Web Search
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
URI: http://eprints.usq.edu.au/id/eprint/20197

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