Using kNN Model for automatic text categorization

G Guo, H Wang, DA Bell, Y Bi, K Greer

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Pages (from-to)423-430
JournalSoft Computing
Issue number5
Publication statusPublished (in print/issue) - 1 Mar 2006

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This paper investigates the strengths of k-nearest neighbour (k-NN) and Rocchio learning algorithms, and develops a new learning method called kNNModel for text categorization, which combines the strengths of KNN with those of Rocchio. A text categorization prototype system was developed within the EU FP5 Intelligent Content Management System (ICONS) project (IST-2001-32429), comprising kNNModel, kNN, Rocchio and Support Vector Machine (SVM). The kNNModel approach provides an effective tool for text indexing, which is an essential component of search engines, and the prototype system is being used as a benchmark system for developing new methods and techniques for text categorization.

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