New approach for field association term dictionary with passage retrieval

Authors:
Elsayed Atlam;Elmarhomy Ghada;Masao Fuketa;Kazuhiro Morita;Jun-Ichi Aoe
Affiliations:
Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan;Department of Information Science and Intelligent Systems, University of Tokushima, Tokushima, Japan
Venue:
ACMOS'07 Proceedings of the 9th WSEAS international conference on Automatic control, modelling and simulation
Year:
2007

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Abstract

Field Association (FA) terms are a limited set of discriminating terms that can specify document fields. Document fields can be decided efficiently if there are many relevant FA terms in that documents. An earlier approach built FA terms dictionary using a WWW search engine, but there were irrelevant selected FA terms in that dictionary because that approach extracted FA terms from the whole documents. This paper proposes a new approach for extracting FA terms using passage (portions of a document text) technique rather than extracting them from the whole documents. This approach extracts FA terms more accurately than the earlier approach. The proposed approach is evaluated for 38, 372 articles from the large tagged corpus. According to experimental results, it turns out that by using the new approach about 24% more relevant FA terms are appending to the earlier FA term dictionary and around 32% irrelevant FA terms are deleted. Moreover, precision and recall are achieved 98% and 94% respectively using the new approach.