Exploiting Manual Indexing to Improve Collection Selection and Retrieval Effectiveness |
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Authors: | James C French Allison L Powell Fredric Gey Natalia Perelman |
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Institution: | (1) Department of Computer Science, University of Virginia, Charlottesville, VA, USA;(2) Corporation for National Research Initiatives, Reston, VA, USA;(3) UC Data Archive & Technical Assistance, University of California, Berkeley, CA, USA |
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Abstract: | Vocabulary incompatibilities arise when the terms used to index a document collection are largely unknown, or at least not well-known to the users who eventually search the collection. No matter how comprehensive or well-structured the indexing vocabulary, it is of little use if it is not used effectively in query formulation. This paper demonstrates that techniques for mapping user queries into the controlled indexing vocabulary have the potential to radically improve document retrieval performance. We also show how the use of controlled indexing vocabulary can be employed to achieve performance gains for collection selection. Finally, we demonstrate the potential benefit of combining these two techniques in an interactive retrieval environment. Given a user query, our evaluation approach simulates the human user's choice of terms for query augmentation given a list of controlled vocabulary terms suggested by a system. This strategy lets us evaluate interactive strategies without the need for human subjects. |
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Keywords: | entry vocabulary collection selection interactive retrieval query augmentation |
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