By Topic

Contextual Concept Language Model for Answering Biomedical Questions

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Qi Sun ; Dept. of Comput. Sci. & Eng., Fudan Univ., Shanghai, China ; Jinguo Yao ; Junyu Niu

In this paper, we utilize MeSH vocabulary to capture concepts of each word appearing in questions and documents and two new methods, contextual concept smoothing language model (CCSLM) and contextual concept language model (CCLM), are proposed to find the answer sentences from biomedical literature to questions proposed by biomedical experts. The concepts employed in the models, instead of keywords, guarantee the high recall. And the contexts of each underlying answer sentence boost the precision of answers to each question. We evaluate both methods on the data collection of TREC Genomics Track 2006. The results indicate our methods are much better than the straightforward method mentioned above. Comparing to the results of Genomics Track 2006, our methods achieve about 10% higher MAP than the mean level of Genomics Track 2006.

Published in:

Computer Science and Information Engineering, 2009 WRI World Congress on  (Volume:7 )

Date of Conference:

March 31 2009-April 2 2009