Attention, intentions, and the structure of discourse
Computational Linguistics
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Automatic text structuring and summarization
Information Processing and Management: an International Journal - Special issue: methods and tools for the automatic construction of hypertext
Extended Boolean information retrieval
Communications of the ACM
TalkMine: a soft computing approach to adaptive knowledge recommendation
Soft computing agents
Theory of Indexing
Towards CST-enhanced summarization
Eighteenth national conference on Artificial intelligence
Learning cross-document structural relationships using boosting
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
A common theory of information fusion from multiple text sources step one: cross-document structure
SIGDIAL '00 Proceedings of the 1st SIGdial workshop on Discourse and dialogue - Volume 10
A comparison of document, sentence, and term event spaces
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
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In this paper, we propose a term association model which extracts significant terms as well as the important regions from a single document. This model is a basis for a systematic form of subjective data analysis which captures the notion of relatedness of different discourse structures considered in the document, without having a predefined knowledge-base. This is a paving stone for investigation or security purposes, where possible patterns need to be figured out from a witness statement or a few witness statements. This is unlikely to be possible in predictive data mining where the system can not work efficiently in the absence of existing patterns or large amount of data. This model overcomes the basic drawback of existing language models for choosing significant terms in single documents. We used a text summarization method to validate a part of this work and compare our term significance with a modified version of Salton's [1].