Improving website user model automatically using a comprehensive lexical semantic resource
|Improving website user model automatically using a comprehensive lexical semantic resource|
|Author(s)||Safarkhani B., Mohsenzadeh M., Rahmani A.M.|
|Published in||2009 International Conference on E-Business and Information System Security, EBISS 2009|
|Keyword(s)||Semantic vectors, User model (Extra: Automatic construction, Domain specific, General purpose, Lexical resources, Lexical semantics, Semantic element, User interests, User model, User models, Vector models, Web personalization, Wikipedia, Wordnet, Electronic commerce, Information systems, Ontology, Taxonomies, World Wide Web, Semantics)|
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Improving website user model automatically using a comprehensive lexical semantic resource is a 2009 conference paper written in English by Safarkhani B., Mohsenzadeh M., Rahmani A.M. and published in 2009 International Conference on E-Business and Information System Security, EBISS 2009.
A major component in any web personalization system is its user model. Recently a number of researches have been done to incorporate semantics of a web site in representation of its users. All of these efforts use either a specific manually constructed taxonomy or ontology or a general purpose one like WordNet to map page views into semantic elements. However, building a hierarchy of concepts manually is time consuming and expensive. On the other hand, general purpose resources suffer from low coverage of domain specific terms. In this paper we intend to address both these shortcomings. Our contribution is that we introduce a mechanism to automatically improve the representation of the user in the website using a comprehensive lexical semantic resource. We utilize Wikipedia, the largest encyclopedia to date, as a rich lexical resource to enhance the automatic construction of vector model representation of user interests. We evaluate the effectiveness of the resulting model using concepts extracted from this promising resource.
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