Chapter 14 BIOMEDICAL TEXT MINING: A SURVEY OF RECENT PROGRESS Matthew S. Simpson Lister Hill National Center for Biomedical Communications United States National Library of Medicine, National Institutes of Health
[email protected] Dina Demner-Fushman Lister Hill National Center for Biomedical Communications United States National Library of Medicine, National Institutes of Health
[email protected] Abstract The biomedical community makes extensive use of text mining tech- nology. In the past several years, enormous progress has been made in developing tools and methods, and the community has been witness to some exciting developments. Although the state of the community is regularly reviewed, the sheer volume of work related to biomedical text mining and the rapid pace in which progress continues to be made make this a worthwhile, if not necessary, endeavor. This chapter pro- vides a brief overview of the current state of text mining in the biomed- ical domain. Emphasis is placed on the resources and tools available to biomedical researchers and practitioners, as well as the major text mining tasks of interest to the community. These tasks include the recognition of explicit facts from biomedical literature, the discovery of previously unknown or implicit facts, document summarization, and question answering. For each topic, its basic challenges and methods are outlined and recent and influential work is reviewed. Keywords: Biomedical information extraction, named entity recognition, relations, events, summarization, question answering, literature-based discovery C.C. Aggarwal and C.X. Zhai (eds.), Mining Text Data, DOI 10.1007/978-1-4614-3223-4_14, 465 © Springer Science+Business Media, LLC 2012 466 MINING TEXT DATA 1.