JOURNAL ARTICLE

Query expansion for microblog retrieval

Abstract

The extreme brevity of Microblog posts (such as 'tweets') exacerbates the well-known vocabulary mismatch problem when retrieving tweets in response to user queries. In this study, we explore various query expansion approaches as a way to address this problem. We use the Web as a source of query expansion terms. We also tried a variation of a standard pseudo-relevance feedback method. Results on the TREC 2011 Microblog test data (TWEETS11 corpus) are very promising – significant improvements are obtained over a baseline retrieval strategy that uses no query expansion. Since many of the TREC queries were oriented towards the news genre, we also tried using only news sites (BBC and NYTIMES) in the hope that these would be a cleaner, less noisy source for expansion terms. This turned out to be counter-productive.

Keywords:
Query expansion Microblogging Computer science Information retrieval Social media Vocabulary Relevance (law) Baseline (sea) Web search query World Wide Web Search engine

Metrics

45
Cited By
5.68
FWCI (Field Weighted Citation Impact)
20
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Information Retrieval and Search Behavior
Physical Sciences →  Computer Science →  Information Systems
Web Data Mining and Analysis
Physical Sciences →  Computer Science →  Information Systems

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