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International Journal on Soft Computing
Article . 2016 . Peer-reviewed
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ZENODO
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License: CC BY
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A Review on Text Mining in Data Mining

Authors: Yogapreethi.N; Maheswari.S;

A Review on Text Mining in Data Mining

Abstract

Data mining is the knowledge discovery in databases and the gaol is to extract patterns and knowledge from large amounts of data. The important term in data mining is text mining. Text mining extracts the quality information highly from text. Statistical pattern learning is used to high quality information. High –quality in text mining defines the combinations of relevance, novelty and interestingness. Tasks in text mining are text categorization, text clustering, entity extraction and sentiment analysis. Applications of natural language processing and analytical methods are highly preferred to turn text into data for analysis. This survey is about the various techniques and algorithms used in text mining.

Keywords

Text mining, knowledge discovery, Data mining

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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