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- W2342282911 abstract "Text mining, sometimes alternately referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Text mining is the discovery of interesting knowledge in text documents. Many data mining techniques have been proposed for mining useful patterns in text documents. It is a challenging issue to find accurate knowledge (or features) in text documents to help users to find what they want. In existing, Information Retrieval (IR) provided many term-based methods to solve this challenge. The term-based methods suffer from the problems of polysemy and synonymy. The polysemy means a word has multiple meanings, and synonymy is multiple words having the same meaning. In proposed to use pattern (or phrase)-based approaches should perform better than the term-based ones. The proposed approach can improve the accuracy of evaluating term weights because discovered patterns are more specific than whole documents. Index Terms: Text mining, text classification, pattern mining, pattern evolving, information filtering." @default.
- W2342282911 created "2016-06-24" @default.
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- W2342282911 date "2013-01-01" @default.
- W2342282911 modified "2023-09-27" @default.
- W2342282911 title "Mining the Text Documents Using Phrase Based Tokenizer Approach" @default.
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