Paper Info
Title
Effective sentence retrieval based on query-independent evidence
Abstract
In this paper we propose an effective sentence retrieval method that consists of incorporating query-independent features into standard sentence retrieval models. To meet this aim, we apply a formal methodology and consider different query-independent features. In particular, we show that opinion-based features are promising. Opinion mining is an increasingly important research topic but little is known about how to improve retrieval algorithms with opinion-based components. In this respect, we consider here different kinds of opinion-based features to act as query-independent evidence and study whether this incorporation improves retrieval performance. On the other hand, information needs are usually related to people, locations or organizations. We hypothesize here that using these named entities as query-independent features may also improve the sentence relevance estimation. Finally, the length of the retrieval unit has been shown to be an important component in different retrieval scenarios. We therefore include length-based features in our study. Our evaluation demonstrates that, either in isolation or in combination, these query-independent features help to improve substantially the performance of state-of-the-art sentence retrieval methods.
Year
DOI
Venue
2012
10.1016/j.ipm.2012.01.007
Inf. Process. Manage.
Keywords
DocType
Volume
opinion-based feature,standard sentence retrieval model,query-independent evidence,retrieval unit,retrieval performance,retrieval algorithm,query-independent feature,state-of-the-art sentence retrieval method,different retrieval scenario,effective sentence retrieval method,different query-independent feature,opinion mining
Journal
48
Issue
ISSN
Citations 
6
0306-4573
2
PageRank 
References 
Authors
0.36
26
2
Name
Order
Citations
PageRank
Ronald T. Fernández1333.78
David E. Losada232640.63