Abstract
In this paper we present a constrained hidden markov model based approach for extracting non-explicit citing sentences in research articles. Our method involves first independently training a separate HMM for each citation in the article being processed and then performing a constrained joint inference to label non-explicit citing sentences. Results on a standard test collection show that our method significantly outperforms the baselines and is comparable to the state of the art approaches.
| Original language | English (US) |
|---|---|
| Title of host publication | SIAM International Conference on Data Mining 2014, SDM 2014 |
| Editors | Mohammed J. Zaki, Arindam Banerjee, Srinivasan Parthasarathy, Pang Ning-Tan, Zoran Obradovic, Chandrika Kamath |
| Publisher | Society for Industrial and Applied Mathematics Publications |
| Pages | 361-369 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781510811515 |
| DOIs | |
| State | Published - Jan 1 2014 |
| Event | 14th SIAM International Conference on Data Mining, SDM 2014 - Philadelphia, United States Duration: Apr 24 2014 → Apr 26 2014 |
Publication series
| Name | SIAM International Conference on Data Mining 2014, SDM 2014 |
|---|---|
| Volume | 1 |
Other
| Other | 14th SIAM International Conference on Data Mining, SDM 2014 |
|---|---|
| Country | United States |
| City | Philadelphia |
| Period | 4/24/14 → 4/26/14 |
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ASJC Scopus subject areas
- Computer Science Applications
- Software
Cite this
A constrained hidden Markov model approach for non-explicit citation context extraction. / Sondhi, Parikshit; Zhai, Chengxiang.
SIAM International Conference on Data Mining 2014, SDM 2014. ed. / Mohammed J. Zaki; Arindam Banerjee; Srinivasan Parthasarathy; Pang Ning-Tan; Zoran Obradovic; Chandrika Kamath. Society for Industrial and Applied Mathematics Publications, 2014. p. 361-369 (SIAM International Conference on Data Mining 2014, SDM 2014; Vol. 1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A constrained hidden Markov model approach for non-explicit citation context extraction
AU - Sondhi, Parikshit
AU - Zhai, Chengxiang
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In this paper we present a constrained hidden markov model based approach for extracting non-explicit citing sentences in research articles. Our method involves first independently training a separate HMM for each citation in the article being processed and then performing a constrained joint inference to label non-explicit citing sentences. Results on a standard test collection show that our method significantly outperforms the baselines and is comparable to the state of the art approaches.
AB - In this paper we present a constrained hidden markov model based approach for extracting non-explicit citing sentences in research articles. Our method involves first independently training a separate HMM for each citation in the article being processed and then performing a constrained joint inference to label non-explicit citing sentences. Results on a standard test collection show that our method significantly outperforms the baselines and is comparable to the state of the art approaches.
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UR - http://www.scopus.com/inward/citedby.url?scp=84959898491&partnerID=8YFLogxK
U2 - 10.1137/1.9781611973440.41
DO - 10.1137/1.9781611973440.41
M3 - Conference contribution
AN - SCOPUS:84959898491
T3 - SIAM International Conference on Data Mining 2014, SDM 2014
SP - 361
EP - 369
BT - SIAM International Conference on Data Mining 2014, SDM 2014
A2 - Zaki, Mohammed J.
A2 - Banerjee, Arindam
A2 - Parthasarathy, Srinivasan
A2 - Ning-Tan, Pang
A2 - Obradovic, Zoran
A2 - Kamath, Chandrika
PB - Society for Industrial and Applied Mathematics Publications
ER -