Efficient annealing -inspired genetic algorithm for information retrieval from web-document

ABSTRACT

With the huge amount of information available online, the World Wide Web is a fertile area for data mining research. The Web mining research is at the cross road of research from several research is at the cross road of research from several research communities. In this paper, a new adaptive method of mining web documents is proposed. We give an algorithm which combines genetic algorithm and simulated annealing based on vector space model. This algorithm avoids the disadvantage of web documents by using pure genetic algorithm which can not be utilized accurately .Experimental results indicate that this adaptive method significantly improves the performance in retrieval accuracy.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

Additional Classification:
  E. Data
  E.2 DATA STORAGE REPRESENTATIONS
      Subjects: Hash-table representations

  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

General Terms:
Algorithms, Design, Experimentation, Theory

Keywords:
annealing-inspired genetic algorithm, genetic algorithm, information retrieval, simulated annealing