In this paper we have demonstrated that the accuracy of a text retrieval system can be improved if we employ a query expansion method based on explicit relevance feedback that expands the initial query with a structured representation instead of a simple list of words. This representation, named a mixed Graph of Terms, is composed of a directed and an a-directed subgraph and can be automatically extracted from a set of documents using a method for term extraction based on the probabilistic Topic Model. The evaluation of the method has been conducted on a web repository collected by crawling a huge number of web pages from the website ThomasNet.com. We have considered several topics and performed a comparison with a baseline and a less complex structure that is a simple list of words. © Springer-Verlag Berlin Heidelberg 2013.

Colace, F., de Santo, M., Greco, L., Napoletano, P. (2013). Improving Text Retrieval Accuracy by Using a Minimal Relevance Feedback. In Communications in Computer and Information Science (pp. 126-140). Springer [10.1007/978-3-642-37186-8_8].

Improving Text Retrieval Accuracy by Using a Minimal Relevance Feedback

NAPOLETANO, PAOLO
2013

Abstract

In this paper we have demonstrated that the accuracy of a text retrieval system can be improved if we employ a query expansion method based on explicit relevance feedback that expands the initial query with a structured representation instead of a simple list of words. This representation, named a mixed Graph of Terms, is composed of a directed and an a-directed subgraph and can be automatically extracted from a set of documents using a method for term extraction based on the probabilistic Topic Model. The evaluation of the method has been conducted on a web repository collected by crawling a huge number of web pages from the website ThomasNet.com. We have considered several topics and performed a comparison with a baseline and a less complex structure that is a simple list of words. © Springer-Verlag Berlin Heidelberg 2013.
Capitolo o saggio
Probabilistic Topic Model; Query Expansion; Text Retrieval; Computer Science (all)
English
Communications in Computer and Information Science
9783642371851
Colace, F., de Santo, M., Greco, L., Napoletano, P. (2013). Improving Text Retrieval Accuracy by Using a Minimal Relevance Feedback. In Communications in Computer and Information Science (pp. 126-140). Springer [10.1007/978-3-642-37186-8_8].
Colace, F; de Santo, M; Greco, L; Napoletano, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/56747
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