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Data mining a tool for knowledge management
 

Data mining a tool for knowledge management

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Paper presented at SIS 2012 Conference held at NIT Silchar organised by Dr. K C Satpathy

Paper presented at SIS 2012 Conference held at NIT Silchar organised by Dr. K C Satpathy

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    Data mining a tool for knowledge management Data mining a tool for knowledge management Presentation Transcript

    • DATA MINING:A TOOL FOR KNOWLEDGE MANAGEMENTPrepared by: Bhagawati Narzari Dhiru Barman Ridip Jyoti Kalita
    • What We Will Cover Today: Introducing Data Mining Scope of Data Mining Classes of Data Mining Elements of Data Mining Data Mining and Knowledge Management Data Mining in Libraries Bibliomining Conclusion SIS-2012 2
    • Introducing Data Mining Data mining is one process of extracting patterns from data. Data mining involves sorting through large amounts of data and picking out relevant information. Data mining can be used in any organization including library to apply to the two separate processes of knowledge discovery and prediction. Data mining is one of the important parts of Bibliomining, where large amount of data are associated with the library systems in order to aid decision-making or justify services. Data mining and its elements, functions, process and some other involving factors have been discussed in this paper. SIS-2012 3
    • Scope of Data Mining Automated prediction of trends and behaviors: Data mining automates the process of finding predictive information in large databases. Questions that traditionally required extensive hands-on analysis can now be answered directly from the data — quickly. Automated discovery of previously unknown patterns: Data mining tools sweep through databases and identify previously hidden patterns in one step. An example of pattern discovery is the analysis of retail sales data to identify seemingly unrelated products that are often purchased together. SIS-2012 4
    • Traditional Data Mining Process SIS-2012 5
    • Classes of Data Mining Predicting Classification Detection of relations Explicit modeling Clustering Market Basket Analysis Deviation Detection SIS-2012 6
    • Elements of Data Mining Extract, transform, and load transaction data onto the data warehouse system Store and manage the data in a multidimensional database system Provide data access to business analysts and information technology professionals. Analyze the data by application software. Present the data in a useful format, such as a graph or table. SIS-2012 7
    • Possible Questions on Data Mining in LIScData Possible Question Enabling Section ServiceMing in Technolo Belonging BelongingLibrary giesSL. NO.1 “How many books Computer, Acquisition Lending acquired last year Library Section service, regarding science software Document stream” delivery serviceSL. NO.2 “How many Computer, Reference Reference encyclopedias are there Library Section and at present in the library” software Information ServiceSL. NO.3 “How many subscribed Computer, Periodical Section Periodical science journals are Library Service there at present in the software library”SL. NO.4 “Which are the Computer, Bound Periodical Periodical newspaper that has Library Section/Back Service been kept in bound software Volume Section
    • BibliominingA new term to describe the data mining process inlibraries is Bibliomining (Nicholson and Stanton, Inpress). Bibliomining is defined as “the combination ofdata mining, bibliometrics, statistics, and reporting toolsused to extract patterns of behavior-based artifacts fromlibrary systems” (Nicholson, 2002). Instead of behavior-based artifacts, however, this project is usingbibliomining to discover patterns in artifacts contained inand associated with Web pages. The techniques todiscover novel and actionable patterns still apply. SIS-2012 9
    • Conclusion The need and application of data mining has become essential to manage, organize, and disseminate information to the right users at right time. Though it is primarily intended for the business class, still then it has got practical implications in Libraries and Information Centers due to overwhelming growth of literature especially in digital formats. Now-a-days, more and more digital data are being collected, processed, managed and archived in Libraries and Information Centers to suit to the varied need of the user communities every day.
    • THANK YOU SIS-2012 11