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

Algarni, Abdulmohsen and Li, Yuefeng and Tao, Xiaohui ORCID: https://orcid.org/0000-0002-0020-077X (2010) Mining specific and general features in both positive and negative relevance feedback. In: TREC 2010: 19th Text REtrieval Conference: Relevance Feedback Track, 16-19 Nov 2010, Gaithersburg, MD, USA.

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Abstract

User relevance feedback is usually utilized by Web systems
to interpret user information needs and retrieve effective
results for users. However, how to discover useful
knowledge in user relevance feedback and how to wisely
use the discovered knowledge are two critical problems.
However, understanding what makes an individual document
good or bad for feedback can lead to the solution of the previous problem. In TREC 2010, we participated in the Relevance Feedback Track and experimented two models for extracting pseudo-relevance feedback to improve the ranking of retrieved documents. The first one, the main run, was a pattern-based model, whereas the second one, the optional
run, was a term-based model. The two models consisted of two stages: one using relevance feedback provided by TREC’10 to expand queries to extract pseudo-relevance
feedback; one using pseudo-relevance feedback to find useful
patterns and terms according to their relevance and irrelevance judgements to rank documents. In this paper, the
detailed description of those models is presented.

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Item Type:	Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed:	No
Item Status:	Live Archive
Additional Information:	No evidence of copyright restrictions preventing deposit. Paper no. 33.
Faculty/School / Institute/Centre:	Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Faculty/School / Institute/Centre:	Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Date Deposited:	18 May 2011 07:07
Last Modified:	03 Jul 2013 00:39
Uncontrolled Keywords:	survey; user feedback; change management; relevance; ranking
Fields of Research (2008):	08 Information and Computing Sciences > 0806 Information Systems > 080602 Computer-Human Interaction 08 Information and Computing Sciences > 0807 Library and Information Studies > 080703 Human Information Behaviour 17 Psychology and Cognitive Sciences > 1701 Psychology > 170110 Psychological Methodology, Design and Analysis
Fields of Research (2020):	46 INFORMATION AND COMPUTING SCIENCES > 4608 Human-centred computing > 460806 Human-computer interaction 46 INFORMATION AND COMPUTING SCIENCES > 4610 Library and information studies > 461002 Human information behaviour 52 PSYCHOLOGY > 5201 Applied and developmental psychology > 520105 Psychological methodology, design and analysis
Socio-Economic Objectives (2008):	C Society > 93 Education and Training > 9301 Learner and Learning > 930102 Learner and Learning Processes
URI:	http://eprints.usq.edu.au/id/eprint/19094

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