Fuzzy Qualitative Models to Evaluate the Quality on the Web

  • Enrique Herrera-Viedma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3131)


The problem of finding quality information and services on the Web is analyzed. We present two user-centered evaluation methodologies to characterize the quality of the Web documents and Web sites that contain these Web documents. These evaluation methodologies are designed using a fuzzy linguistic approach in order to facilitate the expression of qualitative and subjective judgements. These methodologies allow to obtain quality evaluations or recommendations on the accessed Web documents/sites from linguistic judgements provided by Web visitors. Then, these recommendations can aid other visitors (information or service searchers) to decide which Web recourses to access, that is, to find quality information and services on the Web.


Web documents Web services quality evaluation fuzzy linguistic modelling XML 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aladwani, A.M., Palvia, P.C.: Developing and validating an instrument for measuring user-perceived web quality. Information & Management 39, 467–476 (2002)CrossRefGoogle Scholar
  2. 2.
    Alexander, J., Tate, M.: Teaching critical evaluation skills for World Wide Web resources , rev. (1996),
  3. 3.
    Baeza, R.: Information retrieval in the Web: Beyond current search engines. Int. J. of Approximate Reasoning 34(2-3), 97–104 (2003)zbMATHCrossRefGoogle Scholar
  4. 4.
    Barnes, M.D., et al.: Measuring the relevance of evaluation criteria among health information seekers. Int. J. of Health Psychology 8(1), 71–82 (2003)CrossRefGoogle Scholar
  5. 5.
    Bovee, M., Srivastava, R.J., Mak, B.: A conceptual framework and belief-function approach to assessing overall information quality. Int. J. of Intelligent Systems 18, 51–74 (2003)zbMATHCrossRefGoogle Scholar
  6. 6.
    Griffiths, K.M., Christensen, H.: The quality and accessibility of Australian depression sites on the World Wide Web. Medical J. of Australia 176, 97–104 (2002)Google Scholar
  7. 7.
    Henzinger, M.R., Motwani, R., Silverstein, C.: Chanllenges inWeb search engines. SIGIR Forum 36(2) (2002)Google Scholar
  8. 8.
    Herrera, F., Herrera-Viedma, E.: Aggregation operators for linguistic weighted information. IEEE Trans. on Sys. Man and Cyb. Part. A. Systems & Humans 27, 646–656 (1997)CrossRefGoogle Scholar
  9. 9.
    Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: Direct approach processes in group decision making using linguistic OWA operators. Fuzzy Sets and Systems 79, 175–190 (1996)zbMATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Herrera-Viedma, E.: Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach. J. of the Ame. Soc. for Inf. Sci. and Tech. 52(6), 460–475 (2001)CrossRefGoogle Scholar
  11. 11.
    Herrera-Viedma, E.: An information retrieval system with ordinal linguistic weighted queries based on two weighting elements. Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems 9, 77–88 (2001)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Herrera-Viedma, E., Pasi, G.: Fuzzy approaches to access information on the Web: recent developments and research trends. In: Proc. of Third Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT),Zittau, Germany, pp. 25–31 (2003)Google Scholar
  13. 13.
    Herrera-Viedma, E., Peis, E.: Evaluating the informative quality of documents in SGML format from judgements by means of fuzzy linguistic techniques based on computing with words. Information Processing & Management 39(2), 233–249 (2003)zbMATHCrossRefGoogle Scholar
  14. 14.
    Herrera-Viedma, E., Peis, E., Olvera, M.D., Herrera, J.C., Montero, Y.H.: AWIC 2003. LNCS (LNAI), vol. 2663, pp. 62–72. Springer, Heidelberg (2003)Google Scholar
  15. 15.
    Howitt, A., et al.: An evaluation of general practice websites in the UK. Family Practice 19(5), 547–556 (2002)CrossRefGoogle Scholar
  16. 16.
    Huang, K., Lee, Y.W., Wang, R.Y.: Quality information and knowledge. Prentice Hall, Upper Saddle River (1999)Google Scholar
  17. 17.
    Huizingh, E.K.R.E.: The content and design of Web sites: an empirical study. Information & Management 37(3), 123–134 (2000)CrossRefGoogle Scholar
  18. 18.
    ISO 8402: Quality management and quality assurance–Vocabulary, Int’l Org. for Standardization (1994)Google Scholar
  19. 19.
    Lee, Y.W., Strong, D.M., Kahn, B.K., Wang, R.Y.: AIMQ: A methodology for information quality assessment. Information & Management 40(2), 133–146 (2002)CrossRefGoogle Scholar
  20. 20.
    Meric, F., et al.: Breast cancer on the world wide web: cross sectional survey of quality of information and popularity of websites. British Medical J. 324(7337), 577–581 (2002)CrossRefGoogle Scholar
  21. 21.
    Newman, M.S.: Evaluation criteria and quality control for legal knowledge systems on the Internet: A case study. Law Library J. 91(1), 9–27 (1999)Google Scholar
  22. 22.
    Olsina, L., Rossi, G.: Measuring Web application quality with WebQEM. IEEE Multimedia, 20–29 (October-December 2002)Google Scholar
  23. 23.
    Robbins, S.S., Stylianou, A.C.: Global corporate web sites: an empirical investigation of content and design. Information & Management 40(2), 205–212 (2003)CrossRefGoogle Scholar
  24. 24.
    Smith, A.G.: Applying evaluation to New Zealand goverment websites. Int. J. of Information Management 21, 137–149 (2001)CrossRefGoogle Scholar
  25. 25.
    Strong, D.M., Lee, Y.W., Wang, R.Y.: Data quality in context. Comm. of the ACM 40(5), 103–110 (1997)CrossRefGoogle Scholar
  26. 26.
    Sweetland, J.H.: Reviewing the World Wide Web - Theory versus reality. Library Trends 48(4), 748–768 (2000)Google Scholar
  27. 27.
    Tillotson, J.: Web site evaluation: a survey of undergraduates. Online Information Review 26(6), 392–403 (2002)CrossRefGoogle Scholar
  28. 28.
    Tirri, H.: Search in vain: Challenges for Internet search. IEEE Computer 36(1), 115–116 (2003)Google Scholar
  29. 29.
    Wang, R.Y., Strong, D.M.: Beyond accuracy: What data quality means to data consumers. J. of Manag. Information Systems 12(4), 5–34 (1996)zbMATHGoogle Scholar
  30. 30.
    Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Trans. on Syst., Man, and Cyb. 18, 183–190 (1988)zbMATHCrossRefMathSciNetGoogle Scholar
  31. 31.
    Zadeh, L.A.: The concept of a linguistic variable and its applications to approximate reasoning. Part I. Inf. Sci. 8, 199–249 (1975) ;Part II. Inf. Sci. 8, 301-357 (1975) ,Part III. Inf. Sci. 9 ,43-80 (1975)MathSciNetGoogle Scholar
  32. 32.
    Zadeh, L.A.: A computational approach to fuzzy quantifiers in natural languages. Computers and Mathematics with Applications 9, 149–184 (1983)zbMATHCrossRefMathSciNetGoogle Scholar
  33. 33.
    Zhang, X., Keeling, K.B., Pavur, R.J.: Information quality of commercial Web site home pages: An explorative analysis. In: Proceedings of the Twenty First International Conference on Information Systems. Atlanta, pp. 164–175 (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Enrique Herrera-Viedma
    • 1
  1. 1.Dept. of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain

Personalised recommendations