Chirayu Wongchokprasitti

University of Pittsburgh | Pitt · Department of Biomedical Informatics

Recent efforts in recommender systems research focus increasingly on human factors affecting recommendation acceptance, such as transparency and user control. In this paper, we present IntersectionExplorer, a scalable visualization to interleave the output of several recommender engines with user-contributed relevance information, such as bookmarks...

Recent efforts in recommender systems research focus increasingly on human factors that affect acceptance of recommendations , such as user satisfaction, trust, transparency, and user control. In this paper, we present a scalable visualisation to interleave the output of several recommender engines with human-generated data, such as user bookmarks...

In academic research communities, a typical way to spread ideas or seek for collaboration is through research talks, which might be presented at departmental colloquia or might be in given at conferences. Given a large number of research talks, with some of them happening in parallel, it becomes increasingly harder to focus on those of that are of...

Recommender systems face difficulty in cold-start scenarios where a new user has provided only few ratings. Improving cold-start performance is of great interest. At the same time, the growing number of adaptive systems makes it ever more likely that a new user in one system has already been a user in another system in related domains. To what exte...

This work seeks to enhance a user’s experience in a digital library using group-based social navigation. Ensemble is a portal focusing on computing education as part of the US National Science Digital Library providing access to a large amount of learning materials and resources for education in Science, Technology, Engineering and Mathematics. Wit...

Social navigation and social tagging technologies enable user communities to assemble the collective wisdom, and use it to help community members in finding the right information. However, it takes a significantly-sized community to make a social system truly useful. The question addressed in this paper is whether collaborative information finding...

The study reported in this paper is an attempt to improve content-based recommendation in CoMeT, a social system for sharing information about research colloquia in Carnegie Mellon and University of Pittsburgh campuses. To improve the quality of recommendation in CoMeT, we explored three additional sources for building user profiles: tags used by u...

As the sheer volume of information grows, information overload challenges users in many ways. Large conferences are one of the venues suffering from this overload. Faced with several parallel sessions and large volumes of papers covering diverse areas of interest, conference participants often struggle to identify the most relevant sessions to atte...

Adaptive news systems have become important in recent years. A lot of work has been put into developing these adaptation processes. We describe here an adaptive news system application, which uses an open user model and allow users to manipulate their interest profiles. We also present a study of the system. Our results showed that user profile man...