Bibliomining for automated collection development in a digital library setting: Using data mining to discover web-based scholarly research works

Journal of the American Society for Information Science and Technology

Volumn 54, Issue 12, 2003, Pages 1081-1090

  Nicholson, Scott ^a  

^a SYRACUSE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER PROGRAMMING LANGUAGES; DATA STRUCTURES; DECISION THEORY; DIGITAL LIBRARIES; INTELLIGENT AGENTS; NEURAL NETWORKS; REGRESSION ANALYSIS; WEBSITES;

BIBLIOMINING; CLASSIFICATION TREES; LOGISTIC REGRESSION; NONPARAMETRIC DISCRIMINANT ANALYSIS; PATTERN-MATCHING COMPUTER LANGUAGE; WEB-BASED SCHOLARLY RESEARCH WORKS;

DATA MINING;

EID: 0141860863     PISSN: 15322882     EISSN: None     Source Type: Journal    
DOI: 10.1002/asi.10313     Document Type: Article

References (30)

1. Banerjee, K. (1998). Is data mining right for your library? Computers in Libraries, 18(10), 28-31.
2. Basch, R. (1990). Databank software for the 1990s and beyond. Online, 14(2), 17-24.
3. Beaver, A. (1998, December). Evaluating search engine models for scholarly purposes. D-Lib Magazine. Retrieved November 23, 2002, from http://www.dlib.org/dlib/december98/12beavers.html
4. Berry, M.J., & Linoff, G. (1997). Data mining techniques. New York: Wiley Computer Publishing.
5. Cassel, R. (1995). Selection criteria for Internet resources. C&RL News, 56(2), 92-93.
6. Chau, M. (1999). Web mining technology and academic librarianship: Human-machine connections for the twenty-first century. First Monday 4(6) Retrieved November 23, 2002, from http://www.firstmonday.dk/issues/issue4_6/chau
7. Cleverdon, C. (1962). Report on the testing and analysis of an investigation into the comparative efficiency of indexing system. Cranfield, UK: College of Aeronautics.
8. Dickinson, J. (1984). Science and scientific researchers in modern society (2nd ed.). Paris: Unesco.
9. Evans, G.E. (2000). Developing library and information center collections (4th ed.). Englewood, CO: Libraries Unlimited.
10. Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37-54.
11. Futas, E. (Ed.). (1995). Library acquisition policies and procedures (3rd ed.). Phoenix: Oryx Press.
12. Information Market Observatory (IMO). (1995). The quality of electronic information products and services. Retrieved November 23, 2002, from http://www.midas.gr/info2000/market/fn954ww.zip
13. Hinchliffe, L.J. (1997). Evaluation of information. Retrieved November 23, 2002, from http://alexia.lis.uiuc.edu/~janicke/Eval.html
14. Hinton, G. (1992). How neural networks learn from experience. Scientific American, 267(3), 145-151.
15. Hofman, P., & Worsfold, E. (1999). A list for quality selection criteria: A reference tool for Internet subject gateways. Selection Criteria for Quality Controlled Information Gateways. Retrieved November 23, 2002, from http://www.ukoln.ac.uk/metadata/desire/quality/report-2.html
16. Johnston, M., & Weckert, J. (1990). Selection advisor: An expert system for collection development. Information Technology and Libraries, 9(3), 219-225.
17. Lawrence, S., Giles, C., & Bollacker, K. (1999). Digital libraries and autonomous citation indexing. IEEE Computer, 32(6), 67-71.
18. McCallum, A., Nigam, K., Rennie, J., & Seymore, K. (1999). Building domain-specific search engines with machine learning techniques. In Proceedings of the AAAI-99 spring symposium on intelligent agents in cyberspace. Retrieved November 23, 2002, from http://www.cs.cmu.edu/~mccallum/papers/cora-aaaiss98.ps
19. McGeachin, R.B. (1998). Selection criteria for Web-based resources in a science and technology library collection. Issues in Science and Technology Librarianship, 18. Retrieved November 23, 2002, from http://www.istl.org/98-spring/article2.html
20. Neill, S.D. (1989). The information analyst as a quality filter in the scientific communication process. Journal of Information Science, 15, 3-12.
21. Nentwich, M. (1999). Quality filters in electronic publishing. The Journal of Electronic Publishing, 5(1). Retrieved November 23, 2002, from http://www.press.umich.edu/jep/05-01/nentwich.html
22. Nicholson, S. (2000). Creating an information agent through data mining: Automatic indexing of academic research on the World Wide Web. Unpublished doctoral dissertation. University of North Texas, Denton. Retrieved November 23, 2002, from http://www.bibliomining.org
23. Nicholson, S. (2002). Bibliomining: Data Mining for libraries. Retrieved November 22, 2002, from http://www.bibliomining.org
24. 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 & C. Barko (Eds.), Organizational data mining: Leveraging enterprise data resources for optimal performance. Hershey, PA: Idea Group Publishing
25. Piontek, S., & Garlock, K. (1996). Creating a World Wide Web resource collection. Internet Research: Electronic Networking Applications and Policy, 6(4), 20-26.
26. Pratt, G. F., Flannery, P., & Perkins, C.L.D. (1996). Guidelines for Internet resource selection. C&RL News, 57(3), 134-135.
27. Sharma, S. (1996). Applied multivariate techniques. New York: John Wiley & Sons.
28. Smith, A. (1997). Criteria for evaluation of Internet information resources. Retrieved November 23, 2002, from http://www.vuw.ac.nz/~agsmith/evaln
29. Trybula, W.J. (1997). Data mining and knowledge discovery. In M.E. Williams (Ed.) Annual review of information science and technology (vol. 32, pp. 196-229). Medford, NJ: Information Today.
30. Yulan, H., & Cheung, H. (2000). Mining citation database for the retrieval of scientific publications over the WWW. In Proceedings of Conference on Intelligent Information Processing (pp. 64-72). Beijing, China: Publishing House of Electron.