Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Noun phrases in interactive query expansion and document ranking
Information Retrieval
Random walks on the click graph
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Natural language processing for information retrieval: the time is ripe (again)
Proceedings of the ACM first Ph.D. workshop in CIKM
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Named entity recognition in query
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Methods for Evaluating Interactive Information Retrieval Systems with Users
Foundations and Trends in Information Retrieval
Query suggestions in the absence of query logs
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Combining the Best of Two Worlds: NLP and IR for Intranet Search
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Query suggestion by constructing term-transition graphs
Proceedings of the fifth ACM international conference on Web search and data mining
Automatically structuring domain knowledge from text: An overview of current research
Information Processing and Management: an International Journal
Learning to suggest: a machine learning framework for ranking query suggestions
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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Search is becoming more interactive and query logs are among the commonly used resources to propose search suggestions. An alternative to exploiting logs is the extraction of a domain model based on the actual documents. This is particularly promising when restricting search to an intranet or a Web site where the size of the collection allows the application of full natural language parsing and where the documents can be expected to be virtually spam-free. Using a university Web site as an exemplar, we extract predicate argument structures from documents to acquire a domain model automatically. This domain model can be employed to guide users in information finding. Here we explore different ways of exploiting the initially constructed domain model in interactive search and present a task-based evaluation comparing these methods against a baseline system resembling a standard search interface with no suggestions.