Collaborative Research: Supporting Effective Access Through User-and Topic-Based Language Models

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This collaborative project combines the expertise and experience of Professors Bruce Croft and James Allan at the University of Massachusetts in the development and testing of information retrieval models and systems, with that of Professor Nicholas Belkin at Rutgers University in user modeling and user studies in interactive systems. Tools to support information retrieval and filtering have become common, but in many important respects their performance is mediocre. They make mistakes that are obvious and aggravating to users, and relevant documents are usually mixed with many others that are totally unrelated. These problems significantly lower the productivity and effectiveness of people using the tools, whether in education, science, business, or government. This project investigates a new approach to user and topic modeling that has the potential to significantly improve the effectiveness of information access and filtering. This approach is based on recent research on language models for information retrieval. Language models appear to capture the important aspects of user and domain modeling that have been observed in earlier experiments, and retrieval techniques based on document language models have been shown to be very effective. This project combines standard research methodology using TREC data, experimental and observational user studies in laboratory settings, and studies of the impact in operational environments with many users. It will significantly advance understanding of the impact of user- and topic-models on the important problems of information indexing, retrieval, and access.