A new method for similarity indexing of market basket data
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
KPS: a Web information mining algorithm
WWW '99 Proceedings of the eighth international conference on World Wide Web
Applying genetic algorithms to query optimization in document retrieval
Information Processing and Management: an International Journal
Bibliometric cartography of information retrieval research by using co-word analysis
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Extraction of field-coherent passages
Information Processing and Management: an International Journal
Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Unsupervised learning of mDTD extraction patterns for web text mining
Information Processing and Management: an International Journal
Automatic building of new field association word candidates using search engine
Information Processing and Management: an International Journal
Contextual feature selection for text classification
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Semantic passage segmentation based on sentence topics for question answering
Information Sciences: an International Journal
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In recent years, there has been a tremendous growth of online text information related to the explosive growth of the web which provides a very useful information resource to all types of users who access the Internet for various purposes. The major demand of these users is to get required information within the stipulated time. Humans can recognise subjects of document fields by reading only some relevant specific words called field association words in the field. This paper presents a method of relevant estimation among fields by using field association words. Two methods are proposed in this paper: first is a method of extraction of co-occurrence among fields and the second is a method of judgment of similarity among fields as the methods of relevant estimation among fields. From experimental results, precision of the first method is high when relevance among fields is very high and considering direction of fields, preferable results are obtained in the second method.