Natural language query in the biochemistry and molecular biology domains based on cognition search™.

Abstract

Motivation: With the increasing volume of scientific papers and heterogeneous nomenclature in the biomedical literature, it is apparent that an improvement over standard pattern matching available in existing search engines is required. Cognition Search Information Retrieval (CSIR) is a natural language processing (NLP) technology that possesses a large dictionary (lexicon) and large semantic databases, such that search can be based on meaning. Encoded synonymy, ontological relationships, phrases, and seeds for word sense disambiguation offer significant improvement over pattern matching. Thus, the CSIR has the right architecture to form the basis for a scientific search engine.

Result: Here we have augmented CSIR to improve access to the MEDLINE database of scientific abstracts. New biochemical, molecular biological and medical language and acronyms were introduced from curated web-based sources. The resulting system was used to interpret MEDLINE abstracts. Meaning-based search of MEDLINE abstracts yields high precision (estimated at >90%), and high recall (estimated at >90%), where synonym, ontology, phrases and sense seeds have been encoded. The present implementation can be found at http://MEDLINE.cognition.com.

Contact: Elizabeth.goldsmith@UTsouthwestern.edu Kathleen.dahlgren@cognition.com.