Information fusion for text classification — an experimental comparison

✍ Scribed by Venu Dasigi; Reinhold C. Mann; Vladimir A. Protopopescu

• Book ID: 104161432
• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 142 KB
• Volume: 34
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(00)00171-0

✦ Synopsis

This article reports on our experiments and results on the e!ectiveness of di!erent feature sets and information fusion from some combinations of them in classifying free text documents into a given number of categories. We use di!erent feature sets and integrate neural network learning into the method. The feature sets are based on the `latent semanticsa of a reference library * a collection of documents adequately representing the desired concepts. We found that a larger reference library is not necessarily better. Information fusion almost always gives better results than the individual constituent feature sets, with certain combinations doing better than the others.