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Permalink Reply by DR MD GULNAWAZ AZAM on November 27, 2010 at 6:55

Data mining, the extraction of hidden predictive information from library database, is a powerful new technology with great potential to help libraries focus on the most important information in their data warehouse.Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and presented to a human user, who may be a decision-maker or a data-analyst. The user is confronted with the task of selecting the pieces of knowledge that are of the highest quality or interest according to his or her requirement. Data mining tools predict future trends and behaviors, allowing library to make knowledge based decisions. Data mining techniques are the result of a long process of data manipulation . This evolution began when library data first stored on computer, continued with improvement in data access, and generate techniques that allow users to navigate through their data in real time. In digital library , the data mining is the natural evolution of query and reporting tools. Everyone(who is authentic user of a library) can creates queries and reports.

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Permalink Reply by Vipin Kumar on November 27, 2010 at 7:06

thank u sir

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Permalink Reply by Dr. Deepak Meena on December 28, 2010 at 4:52

Thank you very much sir

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Permalink Reply by Parvez Ahmad on November 27, 2010 at 20:23

Thanks Madam for nice explanation.



pvz

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Permalink Reply by Vipin Kumar on November 28, 2010 at 2:35

thanks mam for nice reply

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Permalink Reply by Dr. Deepak Meena on December 28, 2010 at 4:54

Thanks mam for your good reply

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Permalink Reply by Jayshree Dave on November 28, 2010 at 17:05

Data mining is sorting through data to identify patterns and establish relationships.

Data mining parameters include:

•Association - looking for patterns where one event is connected to another event
•Sequence or path analysis - looking for patterns where one event leads to another later event
•Classification - looking for new patterns (May result in a change in the way the data is organized but that's ok)
•Clustering - finding and visually documenting groups of facts not previously known
•Forecasting - discovering patterns in data that can lead to reasonable predictions about the future (This area of data mining is known as predictive analytics.)
Data mining techniques are used in a many research areas, including mathematics, cybernetics, genetics and marketing. Web mining, a type of data mining used in customer relationship management (CRM), takes advantage of the huge amount of information gathered by a Web site to look for patterns in user behavior.

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Permalink Reply by Vipin Kumar on November 29, 2010 at 7:23

thanks mam for nice reply

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Permalink Reply by Dr. Deepak Meena on December 28, 2010 at 4:55

Thanks Jayshree for your cooperation

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Permalink Reply by RENU GUPTA on November 30, 2010 at 4:19

Hello Sir,

Good definitation

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