Abstract

With explosively increasing amount of information on the Web, users have been getting more bored to seek relevant information. Several studies have introduced adaptive approaches to recognizing personal interests. This paper proposes the collaborative Web browsing system that can support users to share knowledge with other users. Especially, we have focused on user interests extracted from their own activities related to bookmarks. A simple URL based bookmark is provided with semantic and structural information by the conceptualization based on ontology. In order to deal with the dynamic usage of bookmarks, ontology learning based on a hierarchical clustering method can be exploited. As a result of our experiments, about 53.1

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Cite this article

@article{cai-1444,
  author  = {Jason J. Jung},
  title   = {An Application of Collaborative Web Browsing Based on Ontology Learning from User Activities on the Web},
  journal = {Computing and Informatics},
  volume  = {23},
  number  = {4},
  pages   = {337--353},
  year    = {2004},
  issn    = {1335-9150},
  url     = {https://cai.type.sk/content/2004/4/an-application-of-collaborative-web-browsing-based-on-ontology-learning-from-user-activities-on-the-web/}
}
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