Deqing Yang

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Given the users from a social network site, who have been tagged with a set of terms, how can we recommend the movies tagged with a completely different set of terms hosted by another website? Given the users from a website dedicated to Type I and Type II diabetes, how can we recommend the discussion threads from another website dedicated to gestational(More)
Many real applications demand accurate cross-domain recommendation, e.g., recommending a Weibo (the largest Chinese Twitter) user with the products in an e-commerce Web site. Since many social media have rich tags on both items or users, <i>tag-based profiling</i> became popular for recommendation. However, most previous recommendation approaches have low(More)
Who are the most appropriate candidates to receive a call-for-paper or call-for-participation? What session topics should we propose for a conference of next year? To answer these questions, we need to precisely predict research topics of authors. In this paper, we build a MLR (Multiple Logistic Regression) model to predict the topic-following behavior of(More)
Given the plethora of social networking sites, it can be difficult for users to browse too many sites and discover social friends. For example, for a new diabetes patient, how can s/he find the users with similar symptoms on different dedicated sites and form supporting groups with them? Since different sites may use different vocabularies, this problem is(More)
Cross-domain recommendation has attracted wide research interest which generally aims at improving the recommendation performance by alleviating the cold start problem in collaborative filtering based recommendation or generating a more comprehensive user profiles from multiple domains. In most previous cross-domain recommendation settings, explicit or(More)
Who are the best targets to receive a call-for-paper or call-for-participation? What kind of topics should we propose for a workshop or a special issue of next year? Precisely predicting author's topic following behavior, i.e., publishing papers of a certain research topic in future, is essential to answer these questions. In this paper, we aim to model and(More)
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