Temporal pseudo-relevance feedback in microblog retrieval

Whiting, S., Klampanos, I.A. and Jose, J.M. (2012) Temporal pseudo-relevance feedback in microblog retrieval. Lecture Notes in Computer Science, 7224, pp. 522-526. (doi: 10.1007/978-3-642-28997-2_55)

Abstract

Twitter has become a major outlet for news, discussion and commentary of on-going events and trends. Effective searching of Twitter collections poses a number of issues for traditional document-based information retrieval (IR) approaches, such as limited document term statistics and spam. In this paper we propose a novel approach to pseudo-relevance feedback, based upon the temporal profiles of n-grams extracted from the top N relevance feedback tweets. A weighted graph is used to model temporal correlation between n-grams, with a PageRank variant employed to combine both pseudo-relevant document term distribution and temporal collection evidence. Preliminary experiments with the TREC Microblogging 2011 Twitter corpus indicate that through parameter optimisation, retrieval effectiveness can be improved.

• Item Type: Articles
• Additional Information: Presented at ECIR 2012: 34th European conference on Advances in Information Retrieval, Barcelona, Spain, 1-5 April 2012
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Klampanos, Dr Iraklis
• Authors: Whiting, S., Klampanos, I.A., and Jose, J.M.
• Subjects: Q Science > Q Science (General)
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Lecture Notes in Computer Science
• Journal Abbr.: LNCS
• ISSN: 0302-9743
• ISSN (Online): 0302-9743