Leveraging Collaborative Tagging for Web Item Design

The popularity of collaborative tagging sites has created new challenges and opportunities for designers of web items, such as electronics products, travel itineraries, popular blogs, etc. An increasing number of people are turning to online reviews and user-specified tags to choose from among competing items. This creates an opportunity for designers to build items that are likely to attract desirable tags when published. We consider a novel optimization problem: given a training dataset of existing items with their user-submitted tags, and a query set of desirable tags, design the k best new items expected to attract the maximum number of desirable tags. We present algorithms for solving this problem and present experimental results.

Speaker Details

Vagelis Hristidis is an Associate Professor at the Department of Computer Science and Engineering at the University of California, Riverside. He received his PhD in Computer Science from the University of California, San Diego, in 2004. He has received funding from the National Science Foundation, the Department of Homeland Security, Google, IBM and the Kauffman Entrepreneurship Center, including the NSF CAREER Award. His main research addresses the problem of bridging the gap between databases and information retrieval, with particular interest in the interdisciplinary direction of Healthcare Informatics. His work has received more than 2,500 citations according to Google Scholar. He has also edited and co-authored the book “Information Discovery on Electronic Health Records”. For more information, please visit http://www.cs.ucr.edu/~vagelis/.

Vagelis Hristidis
University of California
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Series: Microsoft Research Talks