Hairpins in bookstacks: information retrieval from biomedical text.
Current advances in high-throughput biology are accompanied by a tremendous increase in the number of related publications. Much biomedical information is reported in the vast amount of literature. The ability to rapidly and effectively survey the literature is necessary for both the design and the interpretation of large-scale experiments, and for curation of structured biomedical knowledge in public databases. Given the millions of published documents, the field of information retrieval, which is concerned with the automatic identification of relevant documents from large text collections, has much to offer. This paper introduces the basics of information retrieval, discusses its applications in biomedicine, and presents traditional and non-traditional ways in which it can be used.
Shatkay
Hagit
H
School of Computing, Queen's University, Kingston, Ontario, K7L 3N6, Canada. shatkay@cs.queensu.ca
D000043:Abstracting and Indexing / Q000379:methods; D001185:Artificial Intelligence; D001695:Biology; D001877:Books; D003628:Database Management Systems; D016206:Databases, Bibliographic; D004282:Documentation / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008511:Medicine; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods; D010506:Periodicals as Topic; D009626:Terminology as Topic