Interactive query expansion: a user-based evaluation in a relevance feedback environment
Journal of the American Society for Information Science
Hierarchical presentation of expansion terms
Proceedings of the 2002 ACM symposium on Applied computing
Query chains: learning to rank from implicit feedback
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Information re-retrieval: repeat queries in Yahoo's logs
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Studying the use of popular destinations to enhance web search interaction
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Entity-linking interfaces in user-contributed content: preference and performance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Dynamic term suggestion for searching multilingual school documents
Culture and computing
Algorithmic and user study of an autocompletion algorithm on a large medical vocabulary
Journal of Biomedical Informatics
Structured query suggestion for specialization and parallel movement: effect on search behaviors
Proceedings of the 21st international conference on World Wide Web
When do people use query suggestion? A query suggestion log analysis
Information Retrieval
Web Intelligence and Agent Systems
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We describe two user studies that investigate organization strategies of autocompletion in a known-item search task: searching for terms taken from a thesaurus. In Study 1, we explored ways of grouping term suggestions from two different thesauri (TGN and WordNet) and found that different thesauri may require different organization strategies. Users found Group organization more appropriate for location names from TGN, while Alphabetical works better for object names from WordNet. In Study 2, we compared three different organization strategies (Alphabetical , Group and Composite ) for location name search tasks. The results indicate that for TGN autocompletion interfaces help improve the quality of keywords, Group and Composite organization help users search faster, and is perceived easier to understand and to use than Alphabetical .