Semantic Retrieval for the Accurate Identification of Relational Concepts in Massive Textbases

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

• Type: Conference
• Year: 2006
• Where: ACL
• Authors: Yusuke Miyao, Tomoko Ohta, Katsuya Masuda, Yoshimasa Tsuruoka, Kazuhiro Yoshida, Takashi Ninomiya, Jun-ichi Tsujii
• Keywords: Accurate Retrieval, ACL 2006, ACL 2007, Pre-computed Semantic Annotations, Relational Concepts