Text Classification: process and Algorithms

As the volume of information available on the Internet and corporate increases,there is growing interest in developing tools to help people better find, filter, andmanage these electronic resources. The aim of text classification is to buildsystems which are able to automatically classify documents into categories. Textis cheap but information in the form of knowing what classes a text belongs to isexpensive. Automatic classification of text can provide this information at lowcost. Proper classification of e-documents, online news, emails and digitallibraries needs text mining, machine learning and natural language processingtechniques to get meaningful knowledge. This paper provided a review of textclassification process including documents collection, pre-processing, indexing,feature selection and classification. Moreover, it studied the main algorithms intext classification such as Bayesian classifier, Decision Tree, Decision Rule, Knearest neighbor(KNN), Support Vector Machines(SVMs), Neural Networks,Rocchio’s Algorithm, Fuzzy Correlation and Genetic Algorithms.

کلیدواژه ها:

Text classification ، Algorithm ، Text mining