Using wikipedia content to derive an ontology for modeling and recommending web pages across systems
|Using wikipedia content to derive an ontology for modeling and recommending web pages across systems|
|Author(s)||Chang P.-C., Quiroga L.M.|
|Published in||CEUR Workshop Proceedings|
|Keyword(s)||Agent, Ontology, Recommender, User modeling (Extra: Client sides, Content model, Cross systems, General publics, Recommender, User Modeling, User models, Wikipedia, Agents, Mathematical models, Ontology, Recommender systems, Websites)|
|Article||BASE, CiteSeerX, Google Scholar|
|Web||Ask, Bing, Google (PDF), Yahoo!|
|Download and mirrors|
|Local copy||Not available|
|Remote mirror(s)||Not available|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of conference papers|
Using wikipedia content to derive an ontology for modeling and recommending web pages across systems is a 2009 conference paper written in English by Chang P.-C., Quiroga L.M. and published in CEUR Workshop Proceedings.
In this work, we are building a cross-system recommender at the client side that uses the Wikipedia's content to derive an ontology for content and user modeling. We speculate the collaborative content of Wikipedia may cover many of the topical areas that people are generally interested in and the vocabulary may be closer to the general public users and updated sooner. Using the Wikipedia derived ontology as a shared platform to model web pages also addresses the issue of cross system recommendations, which generally requires a unified protocol or a mediator. Preliminary tests of our system may indicate that our derived ontology is a fair content model that maps an unknown webpage to its related topical categories. Once page topics can be identified, user models are formulated through analyzing usage pages. Eventually, we will formally evaluate the topicality-based user model. Copyright 2004 ACM.
- This section requires expansion. Please, help!
Probably, this publication is cited by others, but there are no articles available for them in WikiPapers.