A Study on Recent Issues in Text Pre-processing and Classification Techniques
Keywords:
Text Data Mining, Text Mining, Stemming algorithms, classification algorithms Truncating, Statistical.Abstract
Data Mining is a significant research area in the field of computer science. Data mining techniques are applied to textual data sets is known as Textual Data Mining (TDM). The TDM consists of two stages Pre-processing and post-processing. In TDM pre-processing faces several issues in various stages such as Tokenization, Stop Word Removal and Stemming. The stemming is one of the pre-processing technique in text mining. It is mainly used to removing inflectional and derivational endings in order to reduce word forms to a common stem. The stemming involves text processing task includes information retrieval, text mining, and natural language processing. In this study, discuss recent issues in text pre-processing classification algorithms in text mining. The study is to show the merits and demerits of text mining techniques.
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