A Fuzzy Embedded GA for Information Retrieving from Related Data Set

  • Yang Yi
  • JinFeng Mei
  • ZhiJiao Xiao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4293)


The arm of this work is to provide a formal model and an effective way for information retrieving from a big related data set. Based upon fuzzy logic operation, a fuzzy mathematical model of 0-1 mixture programming is addressed. Meanwhile, a density function indicating the overall possessive status of the effective mined out data is introduced. Then, a soft computing (SC) approach which is a genetic algorithm (GA) embedded fuzzy deduction is presented. During the SC process, fuzzy logic decision is taken into the uses of determining the genes’ length, calculating fitness function and choosing feasible solution. Stimulated experiments and comparison tests show that the methods can match the user’s most desired information from magnanimity data exactly and efficiently. The approaches can be extended in practical application in solving general web mining problem.


Genetic Algorithm Fuzzy Rule Soft Computing Fuzzy Membership Fuzzy Membership Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Baldonado, M., Chang, C.-C.K., Gravano, L., Paepcke, A.: The Stanford Digital Library Metadata Architecture. Int. J. Digit. Libr. 1, 108–121 (1997)CrossRefGoogle Scholar
  2. 2.
    Choi, D.Y.: Enhancing the Power of Web Search Engines by Means of Fuzzy Query. Decision Support Systems 35, 31–44 (2003)CrossRefGoogle Scholar
  3. 3.
    Etzioni, S., Hanks, T., Jiang, R.M., Karp, O., Waarts, O.: Efficient Information Gathering on The Internet. In: 37th Annual Symposium on Foundations of Computer Science (FOCS 1996) (1996)Google Scholar
  4. 4.
    Montesi, D., Trombetta, A., Dearnley, P.A.: A Similarity Based Relational Algebra for Web and Multimedia Data. Information Process and Management 39, 307–322 (2003)MATHCrossRefGoogle Scholar
  5. 5.
    Pasi, G., Villa, R.: Personalized News Content Programming (PENG): A System Architecture. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 1008–1012. Springer, Heidelberg (2005)Google Scholar
  6. 6.
    Yager, R.: Misrepresentations and Challenges. IEEE Expert: Intelligent Systems and Their Application, pp. 41–42 (August 1994)Google Scholar
  7. 7.
    Yi, Y., Wang, D.W.: Soft Computing for Scheduling with Batch Setup Times and Earliness-tardiness Penalties on Parallel Machines. J. Int. Manuf. 14, 311–322 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yang Yi
    • 1
  • JinFeng Mei
    • 1
  • ZhiJiao Xiao
    • 1
  1. 1.Computer Science DepartmentZhongShan UniversityGuangZhouChina

Personalised recommendations