Search Assistance Using Search Trails
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An NSF funded research project at the
School of Information and Library Science
University of North Carolina at Chapel Hill
Co-PIs: Rob Capra, Jaime Argeullo
NSF Grant No.: 1718295
Duration:2017-2020 (expected)
School of Information and Library Science
University of North Carolina at Chapel Hill
Co-PIs: Rob Capra, Jaime Argeullo
NSF Grant No.: 1718295
Duration:2017-2020 (expected)
Project Goals
When users search for information, they create search trails based on their interactions with the search system. These trails encode valuable information that could benefit a future searcher, including information about the queries issued, results clicked, pages viewed/bookmarked, and information highlighted as being important to the task. Current search engines use these activity traces to improve search result ranking algorithms and query suggestions. In this work, we will research and develop systems to automatically gather search trail information and display it to users as a form of search assistance. We will investigate factors that influence when and how search trails are used, models for predicting when to display search trails and which trails to display in a particular context. The results of this work have the potential to improve a broad range of systems, including web search engines, digital libraries, and enterprise search systems. People
When users search for information, they create search trails based on their interactions with the search system. These trails encode valuable information that could benefit a future searcher, including information about the queries issued, results clicked, pages viewed/bookmarked, and information highlighted as being important to the task. Current search engines use these activity traces to improve search result ranking algorithms and query suggestions. In this work, we will research and develop systems to automatically gather search trail information and display it to users as a form of search assistance. We will investigate factors that influence when and how search trails are used, models for predicting when to display search trails and which trails to display in a particular context. The results of this work have the potential to improve a broad range of systems, including web search engines, digital libraries, and enterprise search systems. People
- Rob Capra, Co-PI
- Jaime Arguello, Co-PI
- Austin Ward, Ph.D student
- Forthcoming
- Capra, R., Arguello, J., Crescenzi, A., and Vardell, E. Differences in the Use of Search Assistance for Tasks of Varying Complexity. In Proceedings of the 38th Annnual International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR'15), 2015.
- Forthcoming
This material is based upon work supported by the National Science Foundation under Grant No. 1718295
Any opitions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.