A document classification method by using field association words
Information Sciences—Informatics and Computer Science: An International Journal
Similarity measurement using term negative weight and its application to word similarity
Information Processing and Management: an International Journal
Developing a new similarity measure from two different perspectives
Information Processing and Management: an International Journal
Documents similarity measurement using field association terms
Information Processing and Management: an International Journal
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Decisions in thesaurus construction and use
Information Processing and Management: an International Journal
Automatic acquisition for sensibility knowledge using co-occurrence relation
International Journal of Computer Applications in Technology
An automatic extraction method of word tendency judgement for specific subjects
International Journal of Computer Applications in Technology
Expert Systems with Applications: An International Journal
Research of fast SOM clustering for text information
Expert Systems with Applications: An International Journal
A novel neighborhood based document smoothing model for information retrieval
Information Retrieval
An incremental construction method of a large-scale thesaurus using co-occurrence information
International Journal of Computer Applications in Technology
Selecting queries from sample to crawl deep web data sources
Web Intelligence and Agent Systems
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By the development of the computer in recent years, calculating a complex advanced processing at high speed has become possible. Moreover, a lot of linguistic knowledge is used in the natural language processing (NLP) system for improving the system. Therefore, the necessity of co-occurrence word information in the natural language processing system increases further and various researches using co-occurrence word information are done. Moreover, in the natural language processing, dictionary is necessary and indispensable because the ability of the entire system is controlled by the amount and the quality of the dictionary. In this paper, the importance of co-occurrence word information in the natural language processing system was described. The classification technique of the co-occurrence word (receiving word) and the co-occurrence frequency was described and the classified group was expressed hierarchically. Moreover, this paper proposes a technique for an automatic construction system and a complete thesaurus. Experimental test operation of this system and effectiveness of the proposal technique is verified.