Towards an integrated maintenance advisor
HYPERTEXT '89 Proceedings of the second annual ACM conference on Hypertext
Experiments with query acquisition and use in document retrieval systems
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Concept learning and heuristic classification in weak-theory domains
Artificial Intelligence
Retrieval performance in Ferret a conceptual information retrieval system
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Improving Retrieval Performance by Relevance Feedback
Improving Retrieval Performance by Relevance Feedback
Automatic Information Organization and Retrieval.
Automatic Information Organization and Retrieval.
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Information retrieval systems that use conceptual indexing to describe the information content perform better than syntactic indexing methods based on words from a text. However, since conceptual indices represent the semantics of a piece of information, it is difficult to extract them automatically from a document, and it is tedious to build them manually. We implemented an information retrieval system that acquires conceptual indices of text, graphics and videotaped documents. Our approach is to use an underlying model of the domain covered by the documents to constrain the usds queries. This facilitates question-based acquisition of conceptual indices: converting user queries into indices which accurately model the content of the documents, and can be reused. We discuss Dedal, a system that facilitates the indexing and retrieval of design documents in the mechanical engineering domain. A user formulates a query to the system, and if there is no corresponding index, Dedal uses the underlying domain model and a set of retrieval heuristics to approximate the retrieval, and ask for confirmation from the user. If the user finds the retrieved information relevant, Dedal acquires a new index based on the query. We demonstrate the relevance and coverage of the acquired indices through experimentation.