Models for retrieval with probabilistic indexing
Information Processing and Management: an International Journal - Modeling data, information and knowledge
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
A document classification method by using field association words
Information Sciences—Informatics and Computer Science: An International Journal
Prosody-based automatic segmentation of speech into sentences and topics
Speech Communication - Special issue on accessing information in spoken audio
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Information Processing and Management: an International Journal
An evaluation method of words tendency depending on time-series variation and its improvements
Information Processing and Management: an International Journal
Documents similarity measurement using field association terms
Information Processing and Management: an International Journal
Word classification and hierarchy using co-occurrence word information
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
Context representation using word sequences extracted from a news corpus
International Journal of Approximate Reasoning
Hot Topic Extraction Based on Timeline Analysis and Multidimensional Sentence Modeling
IEEE Transactions on Knowledge and Data Engineering
Improvement of building field association term dictionary using passage retrieval
Information Processing and Management: an International Journal
Ranking of field association terms using Co-word analysis
Information Processing and Management: an International Journal
Cue phrase classification using machine learning
Journal of Artificial Intelligence Research
BBS based hot topic retrieval using back-propagation neural network
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
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In recent years, there has been a tremendous growth of online text information related to digital libraries, medical diagnostic systems, remote education, news sources and electronic commerce. There is a great need to search and organise huge amount of information in text documents. This paper focuses on word tendencies in documents and presents an automatic extraction method for specific subject. Field judgment is conducted by using field association words and similarity among word tendencies, and other word tendencies are computed with information. Then word tendencies which have the same subject are grouped as one group and the important word tendencies are chosen from that group. Finally, a system suggests word tendencies from specific subjects and fields are implemented. From the experimental result, about 67% of suggested word tendencies have been associated with popular subjects.