A better fitness measure of a text-document for a given set of keywords

  • Sukhamay Kundu
Communications 2B Intelligent Information Retrieval
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1609)


We present a new fitness measure B W (D), for a text-document D against a set of keywords W. The fitness evaluation forms a basic operation in information retrieval. B W (d), differs from other measures in that it accounts for both the frequency of the keywords and their clustering characteristics. It also satisfies the properties of monotonicity and super-additivity, which do not hold for either of the well known Paice-measure and the mixed-max-min measure.


Information retrieval Fitness measure Clustering 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    B.Everitt, Cluster analysis (2nd ed.), Halsted Press, New York, 1980.MATHGoogle Scholar
  2. 2.
    W.B.Frakes and R.Baeza-Yates (eds.), Information Retrieval—data structures and algorithms (1992), Prentice-Hall, NJ.Google Scholar
  3. 3.
    G.J.Klir and B. Yuan, Fuzzy sets and fuzzy logic—theory and applications, Prentice Hall, New Jersey, 1995.Google Scholar
  4. 4.
    S.Kundu, Min-transitivity of fuzzy leftness relationship and its application to decision making, Fuzzy Sets and Systems, 86(1997), pp. 357–367.MATHMathSciNetCrossRefGoogle Scholar
  5. 5.
    C.P.Paice, Soft evaluation of boolean search queries in information retrieval systems, Information Technology Res. Dev. and Appl., 3(1984), pp. 33–42.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Sukhamay Kundu
    • 1
  1. 1.Computer Science DepartmentLouisiana State UniversityBaton RougeUSA

Personalised recommendations