ICTACT Journal on Soft Computing

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

A Web Personalization based on the Sequential Pattern Mining for Improved Web Access


Affiliations
1 Department of Computer Applications, Pioneer College of Arts and Science, India
     

   Subscribe/Renew Journal


The development of information technology, the web has created a big challenge for directing the client to the website pages according to their need. Web page personalization process user’s query and retrieve the search results that corresponds to their interest. Accordingly, the option is to capture the intuition of the client and provide them a list of recommendation. The tedious work is, to find the user’s intuition. The web master of an institution ought to utilize methods of web mining to fetch the user’s intuition. The web usage mining is one the technique to find the users intuition. Web usage mining can provide patterns of usage to the organizations in order to obtain user profiles and therefore they can make easier the website browsing or present specific pages. The recommendation is one of the applications in web usage mining. Recommender systems area unit one of the most common and easily apprehensible applications. There square measure 2 major ways in which most of advice engines work. They can either rely on the properties of the things that every user likes, discovering what else the user might like. In this paper, we tend to propose a recommendation approach that recommends a number of web pages based on user’s interest upon client’s history, from the web log. In this approach, it brings the most accuracy of the web pages to be displayed for the user.

Keywords

Web Usage Mining, Recommendation, Web Personalization, Web Log, Sequential Pattern Mining, Web Mining.
Subscription Login to verify subscription
User
Notifications
Font Size

  • X. Wang, L.T. Wang, X. Xie, J. Jin and M.J. Deen, “A Cloud-Edge Computing Framework for Cyber-Physical-Social Services”, IEEE Communications Magazine, Vol. 55, No. 11, pp. 80-85, 2017.

  • Z. Maamar, G. Alkhatib and S.K. Mostefaoui, “Context-based Personalization of Web Services Composition and Provisioning”, Proceedings of 30th Euromicro Conference, pp. 1-8, 2004.

  • M. Eirinaki and M. Vazirgiannis, “Web Mining for Web Personalization”, ACM Transactions on Internet Technology, Vol. 3, No. 1, pp. 1-27, 2003.

  • S. Khonsha and M.H. Sadreddini, “New Hybrid Web Personalization Framework”, Proceedings of IEEE 3rd International Conference on Communication Software and Networks, pp. 233-238, 2011.

  • V. Viswanathan and K. Ilango, “Ranking Semantic Relationships between Two Entities using Personalization in Context Specification”, Information Sciences, Vol. 207, pp. 35-49, 2012.

  • M. Sah and V. Wade, “Personalised Concept-Based Search on the Linked Open Data”, Journal of Web Semantics, Vol. 36, pp. 32-57, 2016.

  • M. Albanese, A. Picariello, C. Sansone and L. Sansone, “A Web Personalization System based on Web Usage Mining Techniques”, Proceedings of 13th International World Wide Web Conference on Alternate Track Papers and Posters, pp. 288-289, 2004.

  • Bamshad Mobasher, Robert Cooley and Jaideep Srivastava, “Automatic Personalization Based on Web Usage Mining”, Communications of the ACM, Vol. 43, No. 8, pp. 142-151, 2000.

  • A. Jebaraj Ratnakumar, “An Implementation of Web Personalization using Web Mining Techniques”, Journal of Theoretical and Applied Information Technology, Vol. 8, No. 1, pp. 67-73, 2010.

  • Pooja Mehtaa, Brinda Parekh, Kirit Modi, and Paresh Solanki, “Web Personalization Using Web Mining: Concept and Research Issue”, International Journal of Information and Education Technology, Vol. 2, No. 5, pp. 1-7, 2012.

  • C. Ramesh, K.V. Chalapati Rao and A. Goverdhan, “A Semantically Enriched Web Usage Based Recommendation Model”, International Journal of Computer Science and Information Technology, Vol. 3, No. 5, pp. 23-32, 2011.

  • Arundhati Patil, “Personalized Web Page Recommendation Using Ontology”, International Journal on Recent and Innovation Trends in Computing and Communication, Vol. 3, No. 7, pp. 4431-4436, 2013.

  • G. Stumme, B. Berendt and A. Hotho, “Usage Mining for and on the Semantic Web”, Proceedings of International Conference on Data Mining: Next Generation Challenges and Future Directions, pp. 461-480, 2004.

  • B. Berendt, A. Hotho and G. Stumme, “Towards Semantic Web Mining”, Proceedings of International Conference on Semantic Web, pp. 264-278, 2002.

  • R. Agrawal and R. Srikant, “Mining Sequential Patterns”, Proceedings of 11th International Conference on Data Engineering, pp. 3-14, 1995.

  • Nizar Mabroukeh and C.I. Ezeife, “Using Domain Ontology for Semantic Web Usage Mining and Next Page Prediction”, Proceedings of 18th ACM Conference on Information and Knowledge Management, pp. 1677-1680, 2009.


Abstract Views: 225

PDF Views: 0




  • A Web Personalization based on the Sequential Pattern Mining for Improved Web Access

Abstract Views: 225  |  PDF Views: 0

Authors

A. Vaishnavi
Department of Computer Applications, Pioneer College of Arts and Science, India
N. Balakumar
Department of Computer Applications, Pioneer College of Arts and Science, India

Abstract


The development of information technology, the web has created a big challenge for directing the client to the website pages according to their need. Web page personalization process user’s query and retrieve the search results that corresponds to their interest. Accordingly, the option is to capture the intuition of the client and provide them a list of recommendation. The tedious work is, to find the user’s intuition. The web master of an institution ought to utilize methods of web mining to fetch the user’s intuition. The web usage mining is one the technique to find the users intuition. Web usage mining can provide patterns of usage to the organizations in order to obtain user profiles and therefore they can make easier the website browsing or present specific pages. The recommendation is one of the applications in web usage mining. Recommender systems area unit one of the most common and easily apprehensible applications. There square measure 2 major ways in which most of advice engines work. They can either rely on the properties of the things that every user likes, discovering what else the user might like. In this paper, we tend to propose a recommendation approach that recommends a number of web pages based on user’s interest upon client’s history, from the web log. In this approach, it brings the most accuracy of the web pages to be displayed for the user.

Keywords


Web Usage Mining, Recommendation, Web Personalization, Web Log, Sequential Pattern Mining, Web Mining.

References