Users satisfaction through better indexing

Fadaie Araghi, Gholamreza Users satisfaction through better indexing. Cataloging & Classification Quarterly, 2005, vol. 40, n. 2, pp. 5-12. [Journal article (Paginated)]

[thumbnail of Users_Satisfaction_through_better_indexing.pdf]
Preview
PDF
Users_Satisfaction_through_better_indexing.pdf

Download (97kB) | Preview

English abstract

Classification and indexing are two main tools to organize information to serve the users. Information architecture is nothing more than to organize better to achieve this goal. Any user seeks easy access and speed to reach one’s information needs. A classifier/indexer must interpret or estimate the users’ need in the best possible terms. Ranking algorithms–such as Boolean, Vector, or others–is highly recommended and practiced. Some define Retrieval Strategies as a measure of similarity between a quarry and document. Relevance is a criterion for matching aboutness. Aboutness is a criterion for decision-making. Better indexing, as well as better classification, is a key to reaching the ultimate goal in record management. Some suggestions are made for those who create databases, provide information engines, or manage the information.

Item type: Journal article (Paginated)
Keywords: Indexing, Classification, Relevance, Aboutness, Boolean, Vector, Probability, Retrieval
Subjects: I. Information treatment for information services
C. Users, literacy and reading. > CB. User studies.
Depositing user: Gholamreza Fadaie
Date deposited: 25 May 2008
Last modified: 02 Oct 2014 12:11
URI: http://hdl.handle.net/10760/11629

References

1. Jennifer Rowley and John Farrow. (2000). Organizing Knowledge 3rd ed. London: Gower, p. 101.

2. Jiri Hynek. (2002). Document Classification in a Digital Library. Technical Report no. DCSE/TR 2002-04, 40 p., p. 20. Available at: http://www.kiv.zcu.cz/publications/2002/tr-2002-04.pdf

3. David A. Grossman and Ophir Frieder. (1998). Information Retrieval; Algorithms and Heuristic. Boston: Kluwer Academic Publishers, p. 5.

4. Don Lathom. (2002). “Information Architect: Notes toward a New Curriculum,” JASIST 53(10):827.

5. Ricardo Baeza Yates and Berthier Ribeiro-Neto. (1999). Modern Information Retrieval. New York, London: ACM Press; Addison-Wesley, p. 19-21.

6. Grossman and Frieder, Information Retrieval, p. 2.

7. Grossman and Frieder, Information Retrieval, p. 11.

8. Robert M. Losee. (1990). The Science of Information: Measurement and Applications. New York: Academic Press, p. 227.

9. Losee, Science of Information, p. 195.

10. Masse Bloomfield. (2001). “Indexing–Neglected and Poorly Understood,” Cataloging& Classification Quarterly 33(1), 66.

11. Losee, Science of Information, p. 195.

12. Losee, Science of Information, p. 197.

13. Rowley and Farrow, Organizing Knowledge, p. 134; Baeza and Riberto, Modern Information Retrieval, p. 27.

14. Hynek, Document Classification, p. 7.

15. Hynek, Document Classification, p. 8.

16. Ronald R. Yager. (2000). “A Hierachal Document Retrieval Language,” Informational Retrieval 3:357-358.

17. Losee, Science of Information, p. 222.

18. Elaine Svenonius. (1992). “Classification: Prospects, Problems, and Possibilities,” in Classification Research for Knowledge Representation and Organization, p. 5-28.

19. Rowley and Farrow, Organizing Knowledge, p. 24.

20. Baeza and Riberto, Modern Information Retrieval, p. 6.

21. Bloomfield, “Indexing,” p. 67-70.

22. Hynek, Document Classification, p. 18.

23. Hynek, Document Classification, p. 20-21.

24. Hynek, Document Classification, p. 30.

25. Monica Zoperlari Roseti and Claudia Mara Lima Werner, “A Knowledge Acquisition Systematic Within the Domain Analysis Context”, p. 1. Available at: http://www.cos.ufrj.bd~odyssey/publicacoes/wer99f.pdf

26. Hynek, “Document Classification,” p. 9.

27. Fadaie Araghi, Ghoamreza, (2004). “New Scheme for Library Classification,” Cataloging & Classification Quarterly, 38(2).

28. Robert M. Losee. (2002). “Optimal User-Centered Knowledge Organization and Classification Systems: Using Non-Reflected Gray Codes,” Journal of Digital Information 2(3), March. Available at: http://jodi.ecs.soton.ack.uk/Articles/v04/i01/Losee/

29. Hynek, “Document Classification,” p. 34.

30. Grossman and Frieder, Information Retrieval, p. ix.

31. Kurt D. Fenstermacher and Mark Ginsburg. (2003). “Client–Side Monitoring for Web Mining,” Journal of the American Society for Information Science, 54(7).


Downloads

Downloads per month over past year

Actions (login required)

View Item View Item