INTRODUCE ABOUT MYSELF


I am a first-year Ph.D. student at School of Information Sciences, University of Pittsburgh. I received my Master and Bachelor degrees from University of Information Technology. I am very interested in building Adaptive Educational Systems, Intelligent Tutoring Systems, Educational Data Mining, Semantic Information Retrieval, User Modeling and Cognitive Systems. I am currently working at the Personalized Adaptive Web Systems Lab (PAWS). My advisor is Dr. Peter Brusilovsky. Currently, I have been taking part in the projects Open Corpus Personalized Learning and cWadeIn.

Here is my homepage HUNG K CHAU

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Term Extraction For User Profiling: Evaluation By The User

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Suzan Verberne, Maya Sappelli, Wessel Kraaij ( UMAP-2013 ) http://sverberne.ruhosting.nl/papers/swell_umap_cameraready.pdf There are several methods that social information systems use to recommend people to their users. Among these methods, content-based people recommendation is most widely used in many different systems (e.g., Twitter). The systems collect information from users such as publications, blogs, microblogs, or posts to build their profiles in order to do recommendation later. How to build effective user profiles from texts is a difficult task. Most of the studies represent texts as a bag-of-word. Some other try to extract more meaningful terms or phrases. If a system has a good representation for user profile, it will be able to find more accurately similar users so that it can generate good people recommendation to each user. In this paper, Verberne et al. present a study that compares three popular methods of weighting terms for user profiling. The results of this ...
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[Talk Summary 11] Explain and answer: Intelligent systems which can communicate about what they see

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[Talk Summary 4] Entity/Event-level Sentiment Detection and Inference

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