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Prototype-matching methodology applications in Text Mining

Barbro Back, Antonina Kloptchenko, Jarmo Toivonen, Hannu Vanharanta, Ari Visa, Prototype-matching methodology applications in Text Mining. In: International Conference on Information and Knowledge Engineering'02, 2002.

Abstract:

In modern Western culture, text documents are the most common communication vehicle for the exchange of formal knowledge among people. Text contains a vast range of semantic information that is difficult to decipher automatically. Text mining recognizes that complete understanding of natural language text is a long-standing goal of computer science, and focuses on extracting information from text with high relevance to the user needs. There are a number of tasks that a good text analysis tool should solve. In the following paper we consider the types of problems that can be solved using the prototype-matching methodology for text clustering, introduced by our research group. We describe how the developed methodology can be applicable to solve the diverse range of tasks: organization of scientific conferences, news clustering, analyses of financial information, or authorship attribution.

BibTeX entry:

@INPROCEEDINGS{pBaAJHA02a,
  title = {Prototype-matching methodology applications in Text Mining},
  booktitle = {International Conference on Information and Knowledge Engineering'02},
  author = {Back, Barbro and Kloptchenko, Antonina and Toivonen, Jarmo and Vanharanta, Hannu and Visa, Ari},
  year = {2002},
  keywords = {Keywords: text mining, clustering},
}

Belongs to TUCS Research Unit(s): Data Mining and Knowledge Management Laboratory

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