AGENT BASED DATA MINING

AGENT BASED DATA MINING - Parignan08 Data Mining & Ware...

Info iconThis preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon
Parignan’08 [Agent based Data-Mining -project model] Presented by: D.Srikanth T.Suman III / IV B.Tech III / IV B.Tech Information Technology Information Technology Email id: srikanth_devunuri@yahoo.com suman_rsr2003@yahoo.com No: 9949194636 no: 9394712974 KAKATIYA INSTITUTE OF TECHNOLOGY AND KAKATIYA INSTITUTE OF TECHNOLOGY AND SCIENCE, Warangal SCIENCE, Warangal
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Parignan’08 Agent Based Data Mining Agent Based Data Mining ABSTRACT: Data plays a major role in every organization. For every organization, there will be a huge data. For retrieving the required and minute data, we warehouse the data and apply the data mining technique, which is the usual procedure. The main aim of this paper is to demonstrate how we can implement the Data mining in a server-client system with the help of agents to reduce the time complexity that has occurred in normal Data mining process. An agent-based system is a process for building a data warehouse containing application specific information and for mining data there from using agents. The system utilizes functional and resource agents to communicate with distributed databases in order to collect pertinent data. The agents employ multiple strategies for identifying and resolving potential ambiguities involving information gathered by the process .
Background image of page 2
Parignan’08 INTRODUCTION: Data mining is the process of discovering meaningful, new correlation patterns and trends by sifting through large amount of data stored in repositories, using pattern recognition techniques as well as statistical and mathematical techniques. A huge amount of data is stored in databases. With the growth of networked computing, many of these databases are now distributed over a number of computers. A number of systems have already been developed to extract this kind of knowledge from databases. However, in general they discover numeric or propositional knowledge from non-distributed data. We intend to produce a system to discover first- order knowledge from distributed databases. It is necessary to discover the database and its details i.e., from where it is originated. We can get the details by using different techniques using agents. For example by using first order learning techniques. This technique is an agent. There are different programming techniques to determine this first order learning. There is one programming for first order technique i.e., Inductive Logic Programming (ILP) in databases. We intend to deploy the ILP techniques as software agents. A software agent using ILP methods will try to learn knowledge from its assigned database. The assigned databases are our source databases from the organization or the business enterprise. Organizations such as military databases, hospital databases etc., business enterprises
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 4
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 03/26/2011 for the course IT 101 taught by Professor Dontknow during the Spring '07 term at Northern Virginia.

Page1 / 16

AGENT BASED DATA MINING - Parignan08 Data Mining & Ware...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online