Intelligent Agents for Data Mining and Information Retrieval
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20-09-2010, 05:42 PM


Data mining is the process of extracting patterns from data. Data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analyzes offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations.

Data mining can aid direct marketers by providing them with useful and accurate trends about their customers’ purchasing behavior. Based on these trends, marketers can direct their marketing attentions to their customers with more precision. When implemented on high performance client/server or parallel processing computers, data mining tools can analyze massive databases to deliver answers to questions such as, "Which clients are most likely to respond to my next promotional mailing, and why?"

Existing System:

Due to the bulk of information that is present n the system it is not easy to find the desired data. Now this can cause a large loss of time and resources and economy.

Proposed System:

A metasearch engine supports unified access to multiple component search engines. To build a very large-scale metasearch engine that can access up to hundreds of thousands of component search engines, one major challenge is to incorporate large numbers of autonomous search engines in a highly effective manner. To solve this problem, we propose automatic search engine discovery, automatic search engine connection, and automatic search engine result extraction techniques. Here we have tried to enable this system by advanced indexing options for the data searched and collective display of the data from a large bulk of data obtained. We have also added a space and time complexity calculation for the speedy execution and processing of data.

The architecture for the proposed system will be having a number of layers. The first layer is application that the user will be using. The second layer will be the API that calls the method for performing the specific data searching and the third layer will be the engine that performs the searching of the data. The engine will respond to the server according to the API.


Data mining can assist financial institutions in areas such as credit reporting and loan information.
Data mining can aid law enforcers in identifying criminal suspects as well as apprehending these criminals by examining trends in location, crime type, habit, and other patterns of behaviors.

Data mining can assist researchers by speeding up their data analyzing process; thus, allowing them more time to work on other project and implimentations.


Front end : Java
Back end : My SQL
Operating system : LINUX/ Windows
IDE : Net Beans


Processor : Pentium IV OR Above
Primary Memory : 256 MB RAM
Storage : 40 GB Hard Disk
Display : VGA Color Monitor

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13-02-2012, 02:59 PM

to get information about the topic information retrieval notes full report ,ppt and related topic refer the link bellow

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