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 conrmed that the proposed method obtain a better performance than the baseline.
Query Expansion through Weighted Word Pairs
GRECO, LUCA;COLACE, Francesco;DE SANTO, Massimo;
2014-01-01
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 conrmed that the proposed method obtain a better performance than the baseline.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
