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Query Expansion through Weighted Word Pairs.

Authors: GRECO, LUCA; COLACE, Francesco; DE SANTO, Massimo; Paolo Napoletano;

Query Expansion through Weighted Word Pairs.

Abstract

The aim of this paper is to propose a novel query expansion method to improve accuracy of text retrieval systems. Our technique makes use of a minimal explicit relevance feedback to expand an initial query with a structured representation called Weighted Word Pairs. Such a structure can be automatically extracted from a set of documents and uses a method for term extraction based on the probabilistic Topic Model. Evaluation has been conducted on TREC-8 repository and the proposed approach has been compared with other baseline query expansion schemes; experiments confirmed that the proposed method obtain a better performance than the baseline.

Country
Italy
Keywords

Text Retrieval; Query Expansion; explicit relevance feedback; probabilistic relevance feedback, Explicit relevance feedback; Probabilistic topic model; Query expansion; Text retrieval; Software, Explicit relevance feedback; Probabilistic topic model; Query expansion; Text retrieval;

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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