Interactive Term Suggestion for Users of Digital Libraries: Using Subject Thesauri and Co-occurrence Lists for Information Retrieval

Artificial Intelligence Lab, Department of MIS, University of ArizonaThe basic problem in information retrieval is that large scale searches can only match terms specified by the user to terms appearing in documents in the digital library collection. Intermediate sources that support term suggestion can thus enhance retrieval by providing altentative search terms for the user. Term suggestion increases the recall, while interaction enables the user to attempt to not decrease the precision. We are building a prototype user interface that will become the Web interface for the University of Illinois Digital Library Initiative (DLI) testbed. It supports the principle of multiple views, wherc different kinds of term suggestors can be used to complement search and each other. This paper discusses its operation with two complementary term suggestors, subject thesauri and co-occurrence lists, and compares their utility. Thesauri are generatad by human indexers and place selected terms in a subject hierarchy. Co-occurrence lists are generated by computer and place all terms in frequency order of occurrence together. This paper concludes with a discussion of how multiple views can help provide good quality Search for the Net. This is a paper about the design of a retrieval system prototype that allows users to simultaneously combine terms offered by different suggestion techniques, not about comparing the merits of each in a systematic and controlled way. It offers no experimental results