Home | Browse | Search | Credits | About
Register | User Area | DL-Harvest | Help
DLIST

The Basis for Bibliomining: Frameworks for Bringing Together Usage-Based Data Mining and Bibliometrics through Data Warehousing in Digital Library Services

Nicholson, Scott (2005) The Basis for Bibliomining: Frameworks for Bringing Together Usage-Based Data Mining and Bibliometrics through Data Warehousing in Digital Library Services. Information Processing and Management 42(3):pp. 785-804.

Full text available as:
PDF - Requires Adobe Acrobat Reader or other PDF viewer.

Abstract

Preprint - For final version, see Nicholson, S. (2006). The basis for bibliomining: Frameworks for bringing together usage-based data mining and bibliometrics through data warehousing in digital library services. Information Processing and Management 42(3), 785-804. Over the past few years, data mining has moved from corporations to other organizations. This paper looks at the integration of data mining in digital library services. First, bibliomining, or the combination of bibliometrics and data mining techniques to understand library services, is defined and the concept explored. Second, the conceptual frameworks for bibliomining from the viewpoint of the library decision-maker and the library researcher are presented and compared. Finally, a research agenda to resolve many of the common bibliomining issues and to move the field forward in a mindful manner is developed. The result is not only a roadmap for understanding the integration of data mining in digital library services, but also a template for other cross-discipline data mining researchers to follow for systematic exploration in their own subject domains.

EPrint Type:Journal Article (Paginated)
Keywords:Data warehousing, Theory, Library measurement, Library evaluation
Subjects:Data Mining
Bibliometrics
Digital Libraries
ID Code:886
Deposited On:31 May 2005
Alternative Locations:http://authors.elsevier.com/JournalDetail.html?PubID=244&Precis=&popup=
Eprint Statistics:View statistics for this eprint
Tell A Colleague:Tell a colleague about it.

American Civil Liberties Union. (n.d.). USA PATRIOT act. Retrieved May 18, 2004 from http://www.aclu.org/SafeandFree/SafeandFree.cfm?ID=12126&c=207

Barabási, A. (2003). Linked. New York: Penguin Group.

Banerjee, K. (1998). Is data mining right for your library? Computers in Libraries, 18(10), 28-31.

Berry, J., and Linoff, G. (2004). Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2nd edition). Indianapolis, IN: Wiley.

Bollen, J., Luce, R., Vemulapalli, S., and Xu, W. (2003). Usage analysis for the indentification of research trends in digital libraries. D-Lib Magazine 9(5). Available online at http://www.dlib.org/dlib/may03/bollen/05bollen.html.

Borgman, C. L. & Furner, J. (2002). Scholarly communication and bibliometrics. In B. Cronin (Ed.), Annual Review of Information Science and Technology (Vol. 36, pp. 3-72). Medford, NJ: Information Today.

Borgman, C. L. (Ed.) (1990). Scholarly Communication and Bibliometrics, Newbury Park, CA: Sage Publications, Inc.

Börner, K., Chen, C.M., & Boyack, K.W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology 37, 179-255.

Buckland, M. (2003). Five grand challenges for library research. Library Trends, 51(4), 675-686.

Chaudhuri, S. and Dayal, U. (1997). An overview of data warehousing and OLAP technology," SIGMOD Record 26(1), 65-74.

Chen, C. (1999). Visualising semantic spaces and author co-citation networks in digital libraries. Information Processing and Management 35(3),401-420.

Cronin, B. (2001). Bibliometrics and beyond: Some thoughts on web-based citation analysis. Journal of Information Science, 27(1), 1-7.

Eirinaki, M. & Vazirgiannis, M. (2003). Web mining for web personalization. ACM Transactions on Internet Technology 3(1), 1-27.

Geyer-Schulz,A. Hahsler, M., Neumann, A., and Thede, A. (2003). An integration strategy for distributed recommender services in legacy library systems. In M. Schader, W. Gaul, and M. Vichi, editors, Between Data Science and Applied Data Analysis, Proceedings of the 26th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Mannheim, July 22-24, 2002, Studies in Classification, Data Analysis, and Knowledge Organization, pages 412-420. Springer-Verlag, July 2003.

Information Institute of Syracuse (2004). QABuilder. Retrieved May 21, 2004 from http://vrd.org/qabuilder.shtml

Johnson, M. (1999). Archeological Theory: An Introduction. Oxford: Blackwell.

Kao, S. Chang, H., and Lin, C. (2003). Decision support for the academic library acquisition budget allocation via circulation database mining. Information Processing &Management 39(1), 133-148.

Kostoff, R., del Río, J., Humenik, J., García, E., and Ramírez, A. (2001). Citation Mining: Integrating Text Mining and Bibliometrics for Research User Profiling. Journal of the American Society for Information Science and Technology 52(13), 1148-1156.

Limpaa, H. (2003). Privacy-preserving Data Mining. Retrieved May 18, 2004 from http://www.tcs.hut.fi/~helger/crypto/link/data_mining

McClure, C., Lankes, R. D., Gross, M., & Choltco-Devlin, B. (2002). Statistics, Measures, and Quality Standards for Assessing Digital Library Services: Guidelines and Procedures. Syracuse, NY: ERIC Clearinghouse on Information & Technology. Retrieved May 21, 2004 from http://quartz.syr.edu/quality/

McClure, C. (1989). Increasing the usefulness of research for library managers: Propositions, issues, and strategies. Library Trends, 38(2), 280-294.

Michail, A. (1999). Data mining library reuse patterns in user-selected applications. 14th IEEE International Conference on Automated Software Engineering, Washington, DC: IEEE Computer Society, 24-33.

Murphy, D.E. (2003, April 7). Some librarians use shredder to show opposition to new F.B.I. powers. New York Times, pp. A12.

Nicholson, S. & Stanton, J. (2003). Gaining strategic advantage through bibliomining: Data mining for management decisions in corporate, special, digital, and traditional libraries. In H. Nemati and C. Barko (Eds.), Organizational data mining: Leveraging enterprise data resources for optimal performance (pp.247-262). Hershey, PA: Idea Group Publishing, 2003.

Nicholson, S. (2003). The bibliomining process: Data warehousing and data mining for library decision-making. Information Technology and Libraries, 22 (4), 146-151.

Nicholson, S. (2004a). Bibliomining bibliography. The Bibliomining Information Center. Retrieved March 1, 2004, from http://bibliomining.org

Nicholson, S. (2004b). A conceptual framework for the holistic measurement and cumulative evaluation of library services. Journal of Documentation 60(2), 162-182.

Nicholson, S. (2005). A framework for Internet archeology: Discovering use patterns in digital library and Web–based information resources. First Monday 10(2). Retrieved March 23, 2005 from http://www.firstmonday.org/issues/issue10_2/nicholson/index.html

NISO. (2004). Z39.7 library statistics – E-metrics data dictionary. Retrieved May 18, 2004 from http://www.niso.org/emetrics/

Project Counter. (n.d.) Counter – Counting Online Usage of Networked Electronic Resources, Retrieved May 18, 2004 from http://www.projectcounter.org

Sandstrom, P.E. (2001). Scholarly communication as a socioecological system. Scientometrics 51(3), 573-605.

Saracevic, T. & Kantor, P. (1997). Studying the value of library and information services: Part 1, Establishing a theoretical framework. Journal of the American Society for Information Science. 48(6), 527-542.

Srivastava, J., Cooley, R., Deshpande, M., Tan, P.T. (2000). Web usage mining: Discovery and applications of usage patterns from Web data. SIGKDD Explorations(1)2. 12-23.

South, S. (1977). Method and Theory in Historical Archeology. New York: Academic Press.

White, H.D. & McCain, K.W. (1998). Visualizing a discipline: An author co-citation analysis of information science 1972-1995. Journal of the American Society of Information Science, 49(4), 327-355.

White, H.D. & McCain, K.W. (1989). Bibliometrics. In M.E. Williams (Ed.) Annual Review of Information Science and Technology 24. Medford, NJ: Information Today. 99-168.

Wilkinson, D., Thelwall, M., & Li, X. (2003). Exploiting hyperlinks to study academic Web use. Social Science Computer Review, 21(3), 340-351.

Zucca, J. (2003). Traces in the clickstream: Early work on a management information repository at the University of Pennsylvania. Information Technology and Libraries, 22(4), 175-179.

EPrints dLIST, an open access archive for the Information Sciences, is supported by the School of Information Resources and Library Science and Learning Technologies Center, University of Arizona. Established in 2002, dLIST has a global Advisory Board and is a part of the Information Technology & Society Research Lab. Open Archives
Contact: Admin | Donate