The phenomenal growth of Information Technology requires us to elicit, store and maintain huge volumes of data. Analyzing this data for various purposes is becoming increasingly important. Data mining consists of applying data analysis and discovery algorithms that under acceptable computational efficiency limitations, produce a particular enumeration of patterns over the data. We present two techniques based on using Logic programming tools for data mining. Data mining analyzes data by extracting patterns which describe its structure and discovers co-relations in the form of rules. We distinguish analysis methods as visual and non-visual and present one application of each. We explain that our focus on the field of Logic Programming makes some of the very complex tasks related to Web based data mining and dynamic content generation, simple and easy to implement in a uniform framework.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc2677 |
| Date | 12 1900 |
| Creators | Gupta, Anima |
| Contributors | Tarau, Paul, Boukerche, Azzedine, Jacob, Roy T. |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | Text |
| Rights | Use restricted to UNT Community, Copyright, Gupta, Anima, Copyright is held by the author, unless otherwise noted. All rights reserved. |
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