文章基本信息

标题：Semantic Grounding Strategies for Tagbased Recommender Systems
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作者：Frederico Durao ; Peter Dolog
期刊名称：International Journal of Web & Semantic Technology
印刷版ISSN：0976-2280
电子版ISSN：0975-9026
出版年度：2011
卷号：2
期号：4
DOI：10.5121/ijwest.2011.2405
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Recommender systems usually operate on similarities between recommended items or users. Tag based recommender systems utilize similarities on tags. The tags are however mostly free user entered phrases. Therefore, similarities computed without their semantic groundings might lead to less relevant recommendations. In this paper, we study a semantic grounding used for tag similarity calculus. We show a comprehensive analysis of semantic grounding given by 20 ontologies from different domains. The study besides other things reveals that currently available OWL ontologies are very narrow and the percentage of the similarity expansions is rather small. WordNet scores slightly better as it is broader but not much as it does not support several semantic relationships. Furthermore, the study reveals that even with such number of expansions, the recommendations change considerably.
关键词：Semantic grounding; tags; ontologies; recommendation; similarity