Building new field association term candidates automatically by search engine

Authors:
Masao Fuketa;El-Sayed Atlam;Elmarhomy Ghada;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:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2006

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Abstract

With increasing popularity of the Internet and tremendous amount of on-line text, automatic document classification is important for organizing huge amounts of data. 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 FA words and if the frequency rate is high. This paper proposes a method for automatically building new FA words. A WWW search engine is used to extract FA word candidates from document corpora. New FA word candidates in each field are automatically compared with previously determined FA words. Then new FA words are appended to an FA word dictionary. From the experiential results, our new system can automatically appended around 44% of new FA words to the existence FA word Dictionary. Moreover, the concentration ratio 0.9 is also effective for extracting relevant FA words that needed for the system design to build FA words automatically.