Developing an integrated library decision support data warehouse

Bleyberg, M.Z.; Zhu, Dehua; Cole, Karen B.; Bates, Don; Zhan, Weidong

doi:10.1109/icsmc.1999.825319

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…Typically, the data warehouse is separate from the organization's operational databases. KSUL data warehouse [3] included tools for extracting data from multiple operational databases and external sources; for cleaning, transforming and integrating this data; for loading data into the data warehouse; and for periodically refreshing the warehouse. Data in the warehouse is stored and managed by one or more warehouse servers, which present multidimensional views of data to a variety of front-end tools: query tools, report writers, analysis tools, and data mining tools.…”

Section: Introductionmentioning

confidence: 99%

“…Data in the warehouse is stored and managed by one or more warehouse servers, which present multidimensional views of data to a variety of front-end tools: query tools, report writers, analysis tools, and data mining tools. Attempts were also made to apply various architectural alternatives for coupling data mining with relational database systems [3]. Also, a mining computation expressed in SQL is compared to a specialized implementation of the same mining operation i.e.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and Comparison of Data Mining Tools Using Case Study of Library Management System

Bansal¹,

Kaur²

2013

IJIEE

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis and Comparison of Data Mining Tools Using Case Study of Library Management System

Bansal¹,

Kaur²

2013

IJIEE

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“…While the authors documented traditional library statistics gathered from this data, they also discussed a scenario for data mining with a neural network (Su & Needamangala, 2000). Another study in this area occurred at Kansas State University where researchers presented a prototype for a decision support system based on library automation data (Bleyberg, Zhu, Cole, Bates & Zhan, 1999).…”

Section: Integrated Library Systems and Data Warehousesmentioning

confidence: 99%

Gaining Strategic Advantage Through Bibliomining

Nicholson

Stanton

Organizational Data Mining

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Library and information services in corporations, schools, universities and communities capture information about their users, circulation history, resources in the collection and search patterns (Koenig, 1985). 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 chapter, we present a global view of the data generated in libraries, 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. The chapter examines data sources and possible applications of data mining techniques in the library.

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Developing an integrated library decision support data warehouse

Cited by 2 publications

References 2 publications

Analysis and Comparison of Data Mining Tools Using Case Study of Library Management System

Analysis and Comparison of Data Mining Tools Using Case Study of Library Management System

Gaining Strategic Advantage Through Bibliomining

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