Enterprise Software

Evolutionary Feature Selection for Text Documents Using the SVM

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Executive Summary

HILE more and more textual information is available online, effective retrieval is difficult without good indexing and summarization of document content. Document categorization is one solution to this problem. In recent years a growing number of categorization methods and machine learning techniques have been developed and were applied in different contexts. Documents are typically represented as vectors in a features space. Each word in the vocabulary is represented as a separate dimension. The number of occurrences of a word in a document represents the value of the corresponding component in the document's vector. This document representation results in a huge dimensionality of the feature space, which poses a major problem to text categorization.

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