Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Personalization on the Net using Web mining: introduction
Communications of the ACM
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Data Mining and Personalization Technologies
DASFAA '99 Proceedings of the Sixth International Conference on Database Systems for Advanced Applications
World Wide Web network traffic patterns
COMPCON '95 Proceedings of the 40th IEEE Computer Society International Conference
Personalized mining of web documents using link structures and fuzzy concept networks
Applied Soft Computing
Introduction to intelligent techniques for Web personalization
ACM Transactions on Internet Technology (TOIT)
A preference scoring technique for personalized advertisements on Internet storefronts
Mathematical and Computer Modelling: An International Journal
Online Geovisualization with Fast Kernel Density Estimator
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Personalization of web-based systems based on computational intelligence modeling
CEA'10 Proceedings of the 4th WSEAS international conference on Computer engineering and applications
Developing an ontology-supported information integration and recommendation system for scholars
Expert Systems with Applications: An International Journal
Computational intelligence-based personalization of interactive web systems
WSEAS Transactions on Information Science and Applications
Identifying user preferences with Wrapper-based Decision Trees
Expert Systems with Applications: An International Journal
Effective hybrid recommendation combining users-searches correlations using tensors
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
International Journal of Intelligent Information Technologies
Hi-index | 12.05 |
As customers become more skilled in the use of internet, many companies have gradually established their websites with more and more enormous information to get future competition in electronic commerce (EC). However, the miscellaneous information often brings the users at a loss. Web personalization provides a solution to improvement of information overloading on websites. The objective of web personalization is to give users a website they want or need, and thus knowing the needs of users is an important task for content recommendation in web personalization. In this article, we propose a hybrid approach for this task. The proposed approach trains the artificial neural networks to group users into different clusters, and applies the well-established Kano's method to extracting the implicit needs from users in different clusters. Finally, a real case of tour and travel websites applying the approach is presented to demonstrate the improvement of information overloading.