Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/www2010/paper/main/283> ?p ?o. }
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- 283 creator can-wang.
- 283 creator chun-chen.
- 283 creator deng-cai.
- 283 creator jiajun-bu.
- 283 creator kun-yang.
- 283 creator ziyu-guan.
- 283 type InProceedings.
- 283 label "Document Recommendation in Social Tagging Services".
- 283 sameAs 283.
- 283 abstract "Social tagging services allow users to annotate various online resources with freely chosen keywords (tags). They not only facilitate the users in finding and organizing online resources, but also provide meaningful collaborative semantic data which can potentially be exploited by recommender systems. Traditional studies on recommender systems focused on user rating data, while recently social tagging data is becoming more and more prevalent. How to perform resource recommendation based on tagging data is an emerging research topic. In this paper we consider the problem of document (e.g. Web pages, research papers) recommendation using purely tagging data. That is, we only have data containing users, tags, documents and the relationships among them. We propose a novel graph-based representation learning algorithm for this purpose. The users, tags and documents are represented in the same semantic space in which two related objects are close to each other. For a given user, we recommend those documents that are sufficiently close to him/her. Experimental results on two data sets crawled from Del.icio.us and CiteULike show that our algorithm can generate promising recommendations and outperform traditional recommendation algorithms.".
- 283 hasAuthorList authorList.
- 283 isPartOf proceedings.
- 283 keyword "Personalization".
- 283 keyword "recommendation systems".
- 283 title "Document Recommendation in Social Tagging Services".