An evaluation of retrieval effectiveness for a full-text document-retrieval system
Communications of the ACM
Introduction to artificial intelligence
Introduction to artificial intelligence
Knowledge organization and access in a conceptual information system
Information Processing and Management: an International Journal - Artificial Intelligence and Information Retrieval
An approach to natural language for document retrieval
SIGIR '87 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval
EP-X: a demonstration of semantically based search of bibliographic databases
SIGIR '87 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval
Generation and Evaluation of Indexes for Chemistry Articles
Journal of Intelligent Information Systems
A concept-based approach to retrieval from an electronic industrial directory
International Journal of Electronic Commerce - Special section: Diversity in electronic commerce research
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The development of concept-oriented databases using AI knowledge representation schemes is proposed as a step towards improving the precision and recall of information retrieval systems. Currently underway is the augmentation of a 238,000 citation database, Chemical Abstracts (CA) Volume 105, by addition of detailed conceptual information in the form of frames and hierarchies. The initial text data is parsed using natural language processing (NLP) techniques to create frames describing the semantics of the index entries in the database, with the slots in the frames being pointers into a very large semantic network of conceptual objects (956,000 objects). To examine the resultant knowledge base (KB), a simple hypertext system is proposed, with the conceptual information serving as pathways to connect related citations.