User interface directions for the Web
Communications of the ACM
Personalization on the Net using Web mining: introduction
Communications of the ACM
Automatic personalization based on Web usage mining
Communications of the ACM
Communications of the ACM
Concept-based knowledge discovery in texts extracted from the Web
ACM SIGKDD Explorations Newsletter
A vector space model for automatic indexing
Communications of the ACM
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Analysis of navigation behaviour in web sites integrating multiple information systems
The VLDB Journal — The International Journal on Very Large Data Bases
Data mining for hypertext: a tutorial survey
ACM SIGKDD Explorations Newsletter
Adaptive web sites: cluster mining and conceptual clustering for index page synthesis
Adaptive web sites: cluster mining and conceptual clustering for index page synthesis
A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis
INFORMS Journal on Computing
Web personalization integrating content semantics and navigational patterns
Proceedings of the 6th annual ACM international workshop on Web information and data management
Web site improvements based on representative pages identification
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
A hybrid system for concept-based web usage mining
International Journal of Hybrid Intelligent Systems
Interactive Systems. Design, Specification, and Verification
A Formal Approach for User Interaction Reconfiguration of Safety Critical Interactive Systems
SAFECOMP '08 Proceedings of the 27th international conference on Computer Safety, Reliability, and Security
Semantic Web Usage Mining by a Concept-Based Approach for Off-line Web Site Enhancements
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
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The correct web site text content must be help to the visitors to find what they are looking for. However, the reality is quite different, many times the web page text content is ambiguous, without meaning and worst, it don’t have relation with the topic that is shown as the main theme. One reason to this problem is the lack of contents with concept meaning in the web page, i.e., the utilization of words and sentences that show concepts, which finally is the visitor goal. In this paper, we introduce a new approach for improving the web site text content by extracting Concept-Based Knowledge from data originated in the web site itself. By using the concepts, a web page can be rewrite for showing more relevant information to the eventual visitor. This approach was tested in a real web site, showing its effectiveness