Semantic Relation Analysis and Its Application in Cognitive Profiling

Semantic web is an emerging paradigm that has great potential for the management of web content in a meaningful manner. With more and more semantic information appended to web, the web logs can be used to find valuable information about users. Their preferences, characteristics, cognitive capacity, or goals can be interpreted from the patterns of relations between traversed web nodes. A novel approach called semantic relation analysis (SRA) is proposed in this paper to harvest the new opportunities created by semantic web. In this paper, literature about navigational pattern analysis is presented. Example of using SRA in a learning system is also given. Empirical study about SRA showed promising results.

• Type: Conference
• Year: 2007
• Where: ICALT
• Authors: Taiyu Lin, Kinshuk, Sabine Graf
• Keywords: ICALT 2007, Machine Learning, Semantic Relation Analysis, Semantic Web, Traversed Web Nodes