Retrieval performance in Ferret a conceptual information retrieval system

Michael L. Mauldin
1991 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '91  
FERRET is a full text, conceptual information retrieval system that uses a partial understanding of its texts to provide greater precision and recall performance than keyword ,search techniques, It uses a machine-readable dictionary to augment its lexical knowledge and a variant of genetic learning to extend its script database. Comparison of FERRET's retrieval performance on a collection of 1065 astronomy texts using 22 sample user queries with a standard boolean keyword query system showed
more » ... t precision increased from 35 to 48 percent, and recall more than doubled, from 19.4 to 52.4 percent. l%is paper describes the FERRET system's architecture, parsing and matching abilities, and focuses on the use of the the Webster's Seventh dictionary to increase the system's lexical coverage.
doi:10.1145/122860.122896 dblp:conf/sigir/Mauldin91 fatcat:qi6btn7icnfxxibninousfe4xy