Browsing by Author "Mukhopadhyay, Bikash"

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    Application of Data Mining Techniques for Library Management
    (INFLIBNET Centre, 2003-02) Mukhopadhyay, Bikash; Mukhopadhyay, Sripati
    Data mining is a form of artificial intelligence that uses automated processes to find information. Although its use in libraries is to be explored, data mining has been used successfully for several years in the scientific and business communities for tracking behavior of individuals and groups, processing medical information, and a number of other applications. This system has been designed for librarians to help them manage the library easily. Data Mining involves different kinds of technologies, solutions and techniques and because of its pattern-recognition features; it can be applied to a large database. Data mining software can relate one field to the other field in the database. It can be used to analyze the on-line users' behavior and to predict the future potential users. Here, we have applied data mining to library systems using artificial intelligence technology.
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    Data Mining Techniques for Information Retrieval
    (INFLIBNET Centre, Ahmedabad, 2004-02) Mukhopadhyay, Bikash; Mukhopadhyay, Sripati
    Data mining automatically and exhaustively explores very large datasets, consequently uncovering otherwise hidden relationships among data. This technology has been successfully applied in science, health, marketing and finance to aid new discoveries and strengthen markets. In addition, data mining techniques are being applied to discover and organize information from the Web. Unfortunately these advancements in data storage and distribution technology have not been accompanied by respective research in data retrieval technology for a long time. To put it in short: we are now being flooded with data, yet we are starving for knowledge. This need has created an entirely new approach to data processing - the data mining, which concentrates on finding important trends and meta-information in huge amounts of raw data. In this paper the main concepts of data mining and automatic knowledge discovery in databases are presented (clustering, finding association rules, categorisation, statistical analysis).
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