Journal of Information and Knowledge (Formerly SRELS Journal of Information Management)

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Bibliomining Processes for Integrated Library System


Affiliations
1 Central Library, The University of Burdwan, Burdwan 713 107, India
2 Dept. of Computer Science, The University of Burdwan, Burdwan 713 107, India
     

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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. Here, we have applied data mining to library systems which is known as bibliomining. Unfortunately, few libraries have taken advantage of these data as a way to improve customer service, manage acquisition budgets or influence strategic decision making about uses of information in their organizations. In this paper, we present initially data mining, then a short application of data mining in libraries (bibliomining), and the variety of decisions that those data can inform. We describe ways in which library and information managers can use data mining in their libraries, i.e., bibliomining, to understand patterns of behavior among library users and staff members and patterns of information resource use throughout the institution.

Keywords

Data Warehouse, Data Mining, Bibliomining, OLAP.
User
About The Authors

Bikash Mukhopadhyay
Central Library, The University of Burdwan, Burdwan 713 107
India

Sripati Mukhopadhyay
Dept. of Computer Science, The University of Burdwan, Burdwan 713 107
India


Notifications

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  • Guenther (K). Applying data mining principles to library data collection. Computers in Libraries. Vol. 20(4); 2000; p60-63.

  • American Library Association. Code of ethics of the American Library Association. Retrieved January 27, 2002, from http://www.ala.org/alaorg/oif/ethics.html.

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  • Bleyberg (M Z); Zhu D. Cole (K); Bates (D); Zhan (W). Developing an integrated library decision support warehouse. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, Piscataway, NJ. Vol. 2; 1999; p546-551.

  • Chau (M Y). Mediating off-site electronic reference services: Human-computer interactions between libraries and wpeb mining technology. Proceedings of the Fourth International Conference on Knowledge-Based Intelligent Engineering Systems & Allied Technologies, Piscataway, NJ. Vol. 2; 2000; p695-699.


Abstract Views: 358

PDF Views: 3




  • Bibliomining Processes for Integrated Library System

Abstract Views: 358  |  PDF Views: 3

Authors

Bikash Mukhopadhyay
Central Library, The University of Burdwan, Burdwan 713 107, India
Sripati Mukhopadhyay
Dept. of Computer Science, The University of Burdwan, Burdwan 713 107, India

Abstract


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. Here, we have applied data mining to library systems which is known as bibliomining. Unfortunately, few libraries have taken advantage of these data as a way to improve customer service, manage acquisition budgets or influence strategic decision making about uses of information in their organizations. In this paper, we present initially data mining, then a short application of data mining in libraries (bibliomining), and the variety of decisions that those data can inform. We describe ways in which library and information managers can use data mining in their libraries, i.e., bibliomining, to understand patterns of behavior among library users and staff members and patterns of information resource use throughout the institution.

Keywords


Data Warehouse, Data Mining, Bibliomining, OLAP.

References