Paper: Semantic Retrieval For The Accurate Identification Of Relational Concepts In Massive Textbases

ACL ID P06-1128
Title Semantic Retrieval For The Accurate Identification Of Relational Concepts In Massive Textbases
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

This paper introduces a novel framework for the accurate retrieval of relational con- cepts from huge texts. Prior to retrieval, all sentences are annotated with predicate argument structures and ontological iden- tifiers by applying a deep parser and a term recognizer. During the run time, user re- quests are converted into queries of region algebra on these annotations. Structural matching with pre-computed semantic an- notations establishes the accurate and effi- cient retrieval of relational concepts. This framework was applied to a text retrieval system for MEDLINE. Experiments on the retrieval of biomedical correlations re- vealed that the cost is sufficiently small for real-time applications and that the retrieval precision is significantly improved.