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Relevance Feature Discovery for Text Mining

Archana Singh




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In today’s era a huge amount of data is collected in data storehouse. There is difference between the data which is stored and the knowledge which we earn from the data. The change will not happen automatically, that is why the term data mining comes into existence. For data analysis there must be some idea about data but data mining can help us to get deeper idea about the data. Getting idea from the collected data is the main aim of data mining. Human effort for data analysis is used for short interval and for huge data it builds a bottle neck.


It is already know that for extracting knowledge from the raw data, mining technique is apply where generation of patterns is very important task. Same thing of pattern generation is also done in text mining where generation of patterns from the text is required for the information extraction. Although work is different but mining task in text and data is much different. In case of data mining implicit information is present in the dataset: here hidden unknown and hard extraction of information is done in the text. In case of text mining information is not hidden in form of any unknown form where extraction of information is very hard. One more issue in txt mining is the understanding of the knowledge in case of different human wordings, as sentence is different in different cases.

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Software Requirement :   MATLAB

Hardware Requirement :   • Intel Processor 2.0 GHz or above. • 2 GB RAM or more. • 160 GB or more Hard Disk Drive or above.

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