title: Usability survey of biomedical question answering systems.
abstract: We live in an age of access to more information than ever before. This can be a double-edged sword. Increased access to information allows for more informed and empowered researchers, while information overload becomes an increasingly serious risk. Thus, there is a need for intelligent information retrieval systems that can summarize relevant and reliable textual sources to satisfy a user's query. Question answering is a specialized type of information retrieval with the aim of returning precise short answers to queries posed as natural language questions. We present a review and comparison of three biomedical question answering systems: askHERMES (http://www.askhermes.org/), EAGLi (http://eagl.unige.ch/EAGLi/), and HONQA (http://services.hon.ch/cgi-bin/QA10/qa.pl).
authors.affiliation: Department of Information Science, University of Arkansas at Little Rock, Little Rock, AR 72204, USA. mabauer@ualr.edu
authors.forename: Michael A
authors.initials: MA
authors.lastname: Bauer
authors.forename: Daniel
authors.initials: D
authors.lastname: Berleant
mesh_terms: D016208:Databases, Factual; D005103:Expert Systems; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D009323:Natural Language Processing