Web page ranking based on fuzzy and learning automata

ABSTRACT

The main goal of web pages ranking is to find the interrelated pages. In this paper, we introduce an algorithm called FPR-DLA. In the proposed method learning automata is assigned to each web page which its function is determining the weight of hyperlinks between web pages. Also for determining the weight of each web page parameters such as time duration on a web page and the importance of web pages are considered. Time duration on a web page and the importance of web pages are characterized as a fuzzy linguistic variable. The proposed algorithm calculates the rank of each web page as recursive according to the weights of each web page and hyperlinks between web pages. Experimental results show that the proposed method has a considerable efficiency in determining the rank of web pages.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.5 On-line Information Services
          Subjects: Web-based services

General Terms:
Algorithms, Experimentation

Keywords:
fuzzy variable, learning automata, ranking, web mining