Constructing field association words using declinable words and concurrent words

Authors:
El-Sayed Atlam;Kazuhiro Morita;Masoa Fuketa;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
Venue:
CIMMACS'08 Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
Year:
2008

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Abstract

Readers can know the subject of many document fields by reading only some specific Field Association (FA) words. Document fields can be decided efficiently if there are many rank 1 FA words (words that direct connect to terminal fields) and if the frequency rate is high. This paper proposes a new method for increasing rank 1 FA words using declinable words and concurrent words which relate to narrow association categories and eliminate FA word ambiguity. Concurrent words become Concurrent Field Association Words (CFA words) if there is a little field overlap. Usually, efficient CFA words are difficult to extract using only frequency, so this paper proposes weighting according to degree of importance of concurrent words. The new weighting method causes Precision and Recall to be higher than by using frequency alone. Moreover, combining CFA words with FA words allow easy search of fields which can not be searched by using only FA words.