Open Access Open Access  Restricted Access Subscription Access

Web Portal Visits Patterns Predicted by Intuitionistic Fuzzy Approach


Affiliations
1 School of Computing, Bharath University, Selaiyur, Chennai-600073, India
2 School of Computing Sciences, Bharath University, Selaiyur, Chennai-600073, India
 

Web mining is applied to reflect the importance of webpages and to predict the web domain visits of various users. An IF-inference system is developed for this purpose. This paper presents basic notions of web mining with fuzzy inference systems based on the Takagi-Sugeno fuzzy model. At first, it scans the sequences of visits in database once, finds all the weighted frequent items, and produces a sparse matrix for that sequence item set from which basic statistics like moving averages and exponentially smoothing averages are calculated. Then we construct a IF-inference system using intuitionistic approach for predicting the web domain visits. We obtain the results of such system.

Keywords

Web Mining, If-inference System, Web Domain Visits, Fuzzy Logic, Prediction, Sparse Matrix, Moving Averages, Exponential Smoothing
User

  • Cooley R, Mobasher B et al. (1997). Web mining: information and pattern discovery on the world wide web, Proceedings of the 9th IEEE International Conference on Tools With Artificial Intelligence, (ICTAI ’97), Newport Beach, CA.
  • Zaine O, and Han J (1998). WebML: Querying the world wide web for resources and knowledge, Proceedings of the International workshop on web information and data management, WIDM´98, Bethesda.
  • Kuncheva L I (2000). Fuzzy classifier design, A Springer Verlag Company, Germany.
  • Bandemer H, and Gottwald S (1995). Fuzzy sets fuzzy logic, fuzzy methods, John Wiley and Sons Inc., New York.
  • Olej V (2003). Modeling of economics processes by computational intelligence, Hradec Kralove, (in Slovak).
  • Trešl J (1999). Statistical methods and capital market, 1st edition, Prague, (in Czech).
  • Montiel O et al. (2008). Mediative fuzzy logic: A new approach for contradictory knowledge management, Soft Computing, vol 20, No.3, 251–256.
  • Guillaume S (2001). Designing fuzzy inference systems from Data: An Interpretability-oriented review, IEEE Transactions on Fuzzy Systems, vol 9, 426–442.
  • Available From: http://www.wseas.us/e-library/transactions/computers/2010/88-321.pdf
  • Fuzzy Logic Toolbox™ User’s Guide© Copyright 1995–2012, The Math Works, Inc.
  • Available From: http://archive.ics.uci.edu/ml/datasets/MSNBC.com+Anonymous+Web+Data.
  • Availbale From: http://www.mathworks.in/help/matlab/ref/ sparse.html
  • Kumaravel A, and Pradeepa R (2012). On constructing regular expression of web page traversals for efficient filtering, IEEE Conference Publications, 156-160.

Abstract Views: 438

PDF Views: 0




  • Web Portal Visits Patterns Predicted by Intuitionistic Fuzzy Approach

Abstract Views: 438  |  PDF Views: 0

Authors

A. Kumaravel
School of Computing, Bharath University, Selaiyur, Chennai-600073, India
R. Udayakumar
School of Computing Sciences, Bharath University, Selaiyur, Chennai-600073, India

Abstract


Web mining is applied to reflect the importance of webpages and to predict the web domain visits of various users. An IF-inference system is developed for this purpose. This paper presents basic notions of web mining with fuzzy inference systems based on the Takagi-Sugeno fuzzy model. At first, it scans the sequences of visits in database once, finds all the weighted frequent items, and produces a sparse matrix for that sequence item set from which basic statistics like moving averages and exponentially smoothing averages are calculated. Then we construct a IF-inference system using intuitionistic approach for predicting the web domain visits. We obtain the results of such system.

Keywords


Web Mining, If-inference System, Web Domain Visits, Fuzzy Logic, Prediction, Sparse Matrix, Moving Averages, Exponential Smoothing

References





DOI: https://doi.org/10.17485/ijst%2F2013%2Fv6iS5%2F33353