Usability survey of biomedical question answering systems

被引：20
|
作者：
Bauer, Michael A. [1 ,2 ]
Berleant, Daniel [1 ]
机构：
[1] Univ Arkansas, Dept Informat Sci, Little Rock, AR 72204 USA
[2] Univ Arkansas Med Sci, Little Rock, AR 72205 USA
来源：
HUMAN GENOMICS | 2012年 / 6卷
关键词：
COMPLEX CLINICAL QUESTIONS;
D O I：
10.1186/1479-7364-6-17
中图分类号：
Q3 [遗传学];
学科分类号：
071007 ; 090102 ;
摘要：
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).
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页数：4
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