Extracting Peculiar Data from Multidatabases Using Agent Mining
S.Shahar Banu1, V.Saravanan2, R. Shriram3

1S.Shahar Banu, Assistant Prof, B.S. Abdul Rahman University, Chennai (Tamil Nadu), India.
2V.Saravanan, Professor & Director, Department of Computer Applications, Sri Venkateswara College of Computer Applications and Management, Chennai (Tamil Nadu), India.
3Dr. R. Shriram, Professor, Department of CSE, B.S. Abdul Rahman University, Chennai (Tamil Nadu), India.

Manuscript received on 21 March 2013 | Revised Manuscript received on 28 March 2013 | Manuscript published on 30 March 2013 | PP: 187-189 | Volume-2 Issue-1, March 2013 | Retrieval Number: A0539032113/2013©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Data mining is a broad term that describes the search to extract some meaningful information from data that is unformatted and either unstructured or partially structured Similarly, Fayyad et. al. described it as “The nontrivial process identifying valid, novel, potentially useful, and ultimately understandable patterns in data” . Data mining is also known as knowledge discovery, knowledge extraction, information harvesting, data archeology, and data pattern processing. Although most algorithms provide some unique implementation of each phase, there are several common steps to achieve the goal of identifying patterns in data. Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information – information that can be used to increase revenue, cuts costs, or both. This paper discusses the peculiar data mining and agent mining. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified.
Keywords: Data Mining Peculiar Mining, Agent Based System, Multi Agent .

Scope of the Article: Data Mining