Data Mining and Knowledge Engineering

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Karnaugh Map Model for Mining Association Relationships in Web Content Data:Hypertext


Affiliations
1 Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal, M.P, India
2 Department of Mathematics, Maulana Azad National Institute of Technology, Bhopal, M.P, India
     

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Web content mining refers to description and discovery of useful information from the web contents/data/documents. Hypertext is one of the most common web content data that has hyperlinks in addition to text. These are modeled with multiple levels of details depending on the application. In this paper Karnaugh map model for multilevel association rule mining has been developed to investigate association relationships among hypertexts of a web site. Karnaugh map model needs single scan of data and stores the information in the form of frequency. Model adopts progressively deepening approach for finding large text sets by utilizing karnaugh map logic for finding frequent text sets at each level of abstraction. Frequent texts sets are generated by the karnaugh map model are used to discover strong association relationships among hypertexts at different levels of abstraction. Further the rules are categorized under three categories and their behavior is studied across the level of abstractions.

Keywords

Karnaugh Map Model, Multilevel Association Rules, Association Relationships, Frequent Text Set.
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  • Karnaugh Map Model for Mining Association Relationships in Web Content Data:Hypertext

Abstract Views: 253  |  PDF Views: 2

Authors

Vikrant Sabnis
Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal, M.P, India
Neelu Khare
Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal, M.P, India
R. S. Thakur
Department of Computer Applications, Maulana Azad National Institute of Technology, Bhopal, M.P, India
K. R. Pardasani
Department of Mathematics, Maulana Azad National Institute of Technology, Bhopal, M.P, India

Abstract


Web content mining refers to description and discovery of useful information from the web contents/data/documents. Hypertext is one of the most common web content data that has hyperlinks in addition to text. These are modeled with multiple levels of details depending on the application. In this paper Karnaugh map model for multilevel association rule mining has been developed to investigate association relationships among hypertexts of a web site. Karnaugh map model needs single scan of data and stores the information in the form of frequency. Model adopts progressively deepening approach for finding large text sets by utilizing karnaugh map logic for finding frequent text sets at each level of abstraction. Frequent texts sets are generated by the karnaugh map model are used to discover strong association relationships among hypertexts at different levels of abstraction. Further the rules are categorized under three categories and their behavior is studied across the level of abstractions.

Keywords


Karnaugh Map Model, Multilevel Association Rules, Association Relationships, Frequent Text Set.