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Data Mining Techniques for Information Retrieval
| Content Provider | Inflibnet's Institutional Repository |
|---|---|
| Author | Mukhopadhyay, Bikash Mukhopadhyay, Sripati |
| Abstract | Data mining automatically and exhaustively explores very large datasets, consequently uncovering otherwise hidden relationships among data. This technology has been successfully applied in science, health, marketing and finance to aid new discoveries and strengthen markets. In addition, data mining techniques are being applied to discover and organize information from the Web. Unfortunately these advancements in data storage and distribution technology have not been accompanied by respective research in data retrieval technology for a long time. To put it in short: we are now being flooded with data, yet we are starving for knowledge. This need has created an entirely new approach to data processing - the data mining, which concentrates on finding important trends and meta-information in huge amounts of raw data. In this paper the main concepts of data mining and automatic knowledge discovery in databases are presented (clustering, finding association rules, categorisation, statistical analysis). |
| File Format | |
| ISBN | 8190082582 |
| Language | English |
| Publisher | INFLIBNET Centre |
| Publisher Place | Ahmedabad |
| Access Restriction | Open |
| Subject Keyword | Data Mining Text Mining Web Searching Natural Language Processing Machine Learning |
| Content Type | Text |
| Resource Type | Article |
