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Lundquist, Carol; Frieder, Ophir; Holmes, David O.; Grossman, David – Journal of the American Society for Information Science, 1999
Describes a scalable, parallel, relational database-drive information retrieval engine. To support portability across a wide range of execution environments, all algorithms adhere to the SQL-92 standard. By incorporating relevance feedback algorithms, accuracy is enhanced over prior database-driven information retrieval efforts. Presents…
Descriptors: Database Design, Database Management Systems, Feedback, Information Management

Deogun, Jitender S.; Raghavan, Vijay V. – Information Processing and Management, 1988
Discusses the motivation for integrating information retrieval and database management systems, and proposes a probabilistic retrieval model in which records in a file may be composed of attributes (formatted data items) and descriptors (content indicators). The details and resolutions of difficulties involved in integrating such systems are…
Descriptors: Database Management Systems, Feedback, Information Retrieval, Mathematical Models

Morrissey, J. M.; And Others – Information Processing and Management, 1986
Proposes a "Model of Querying" for users of office filing facilities and discusses its motivation, aspects, attributes, and advantages. A review of current information systems and attempts to combine information retrieval, artificial intelligence, and database management techniques leads to conclusion that no resultant system is adequate…
Descriptors: Artificial Intelligence, Comparative Analysis, Database Management Systems, Databases