Feature Selection and Representation in Text Classification
نویسنده
چکیده
Text classification remains an important practical application of both modern machine learning (ML) and natural language processing (NLP) techniques. The influence of these disparate areas of research has contributed much to the success of current state of the art classification methods. This essay provides an overview of the field of text classification, and investigates in particular the topic of feature representation, which is concerned with how a characterization of the document to be classified is obtained. It is here that both ML and NLP can play a large role, and this essay argues that encouraging collaboration between the two will result in superior classification performance.
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