Automated Text Categorization Using Support Vector Machine

In this paper, we study the use of support vector machine in text categorization. Unlike other machine learning techniques, it allows easy incorporation of new documents into an existing trained system. Moreover, dimension reduction, which is usually imperative, now becomes optional. Thus, SVM adapts e ciently in dynamic environments that require frequent additions to the document collection. Empirical results on the Reuters-22173 collection are also discussed.

• Type: Conference
• Year: 1998
• Where: ICONIP
• Authors: James Tin-Yau Kwok
• Keywords: ICONIP 1998, ICONIP 2007, Machine Learning Techniques, Support Vector Machine, Text Categorization