Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
11-2005
Abstract
In this paper, we present a principled method for accurately extracting coherent relevant passages of variable lengths using HMMs. We show that with appropriate parameter estimation, the HMM method outperforms a number of strong baseline methods on two data sets.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management, October 31 - November 5, 2005, Bremen, Germany
First Page
289
Last Page
290
ISBN
9781595931405
Identifier
10.1145/1099554.1099631
Publisher
ACM
City or Country
Bremen, Germany
Citation
JIANG, Jing and ZHAI, ChengXiang.
Accurately Extracting Coherent Relevant Passages Using Hidden Markov Models. (2005). CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management, October 31 - November 5, 2005, Bremen, Germany. 289-290.
Available at: https://ink.library.smu.edu.sg/sis_research/1257
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1145/1099554.1099631
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons
