The projects goal is the research and development of new Business Intelligence (BI) tools for focused search and retrieval, which will support analysis and decision-making related to energy conservation and management.
Postdoctoral fellow: Dr. Jane E. Mason, David R. Cheriton School of Computer Science, University of Waterloo
Lead faculty member: Dr. Frank Tompa, David R. Cheriton School of Computer Science, University of Waterloo
Business Intelligence (BI) refers to computer-based techniques that facilitate the use of information within organizations to make informed decisions and to run operations effectively based on available data. Our goal is the research and development of new BI tools for focused search and retrieval, which will support analysis and decision-making related to energy conservation and management. Such tools will also have wide applicability to business analytics in general.
Focused retrieval, such as passage retrieval, question answering, and XML element retrieval, provides more direct access to relevant information by locating and retrieving relevant document passages, providing the user with results that are tailored to the request at hand. We propose representing documents using fixed-length contiguous byte (character) n-grams. Many information retrieval and natural language processing applications make successful use of n-gram-based representations, but to the best of our knowledge, their use has not been extensively investigated in the context of focused retrieval.