University of Illinois computer science alumnus Tianyi Wu was named the runner-up for the 2011 ACM SIGKDD Ph.D. Dissertation Award for his thesis “A Framework for Promotion Analysis in Multi-Dimensional Space”. The annual award recognizes excellent research by doctoral candidates in the field of data mining and knowledge discovery.
Wu’s work involves the use of a novel class of data mining problems, called promotion analysis, for marketing purposes. His thesis discusses how promotion analysis can be used for promoting a given product in a multi-dimensional space by leveraging object ranking information. Wu’s key observation is that while most products may not be highly ranked in the global space, where all products are compared by all aspects, there often exist interesting and meaningful local spaces in which the given product becomes prominent. Therefore, Wu’s goal is to break down the data space and discover the most interesting local spaces in an effective and efficient way.
The promotion analysis problem is highly practical and useful in a wide spectrum of decision support applications, says Wu. Typical application examples include merit discovery, product positioning and customer targeting, object profiling and summarization, identification of interesting features, and explorative search of objects.
Toward this end, Wu’s work develops a general, principled promotion analysis framework. His thesis proposes not only a unified query model to accommodate various scoring functions and redundancy-aware semantics, but also a statistical method to avoid spurious promotion results. His thesis opens up future work in areas like information network analysis, text mining, and probabilistic data management.
Wu is currently works as an Applied Researcher at Microsoft, focused on the Bing technologies. His Ph.D. advisor was computer science professor Jiawei Han.