Accession Number:

ADA581528

Title:

Frequent Itemset Mining for Query Expansion in Microblog Ad-hoc Search

Descriptive Note:

Conference paper

Corporate Author:

WATERLOO UNIV (ONTARIO)

Report Date:

2012-11-01

Pagination or Media Count:

5.0

Abstract:

The high volume of Tweets arriving every second and the requirement to index them in real time emphasize the importance of the computational complexity of algorithms used to process them. In this paper, we investigate the use of Frequent Itemsets Mining to quickly discover patterns that can later be used for query expansion. Frequent Itemsets Mining FIM has been highly adopted to mine data streams because of its computational simplicity and the possibility to parallelize some of its steps. Initial experiments using the TREC 2011 Microblogs track queries showed that it is possible to improve the performance of BM25, however this was not the case with the 2012 queries. Our analysis of the difference in performance provides insight about how to make best use of FIM for microblog search.

Subject Categories:

  • Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE