A STUDY ON TEXT CLASSIFICATION TECHNIQUES AND APPROACHES
Keywords:
Data Mining, Clustering, Classification, Similarity Measure, Feature SelectionAbstract
The world around us is changing very rapidly each day. The main cause of this rapid change is the growth of technologies like internet, world wide web, mobile communications etc. These new technologies gave rise to the concept of data driven era in which we live today. Data refers to knowledge or information that is represented in different formats. Data mining effectively mines information useful for various application domains. The input dataset for mining is collected from the application domain which is huge and may contain noisy and irrelevant data. To remove the irrelevant data the dataset is subjected to cleaning and pre-processing which results a complete dataset for extraction of information. The data set is then reduced and the useful features are identified. Using this transformed data mining process is done which gives the researcher some information which is later produced in an understandable form according to the application domain perspectives. It is a complex and innovative field of research. This study focuses on various techniques and methods adopted for each phase in clustering task. A comparative study of various similar methods are also done by which the efficient methods were identified.
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