TY - GEN
T1 - A discourse coherence model for analyzing Chinese students' essay
AU - Huang, Guimin
AU - Tan, Min
AU - Huang, Sirui
AU - Mo, Ruyu
AU - Zhou, Ya
N1 - Funding Information:
This work is supported by the National Natural Science Foundation of China (No. 61662012) as well as the Foundation of Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology, No. CRKL150105) and the scientific research technological development Project of Guilin (No. 2016010406-3) and the Innovation Project of GUET Graduate Education (No. 2016YJCX16).
Publisher Copyright:
© 2017 IEEE.
PY - 2017
Y1 - 2017
N2 - Many attempts on improving entity grid model have been made and boost the research on text coherence. However, only a few of them applied it to noisy data domain and students' essay. Thus, we proposed a novel discourse coherence model, which is based on entity grid model, to evaluate coherence on Chinese students' essay. In allusion to the feature of Chinese students' essay, frequently using lexical repetition and coreference methods in coherence essay, we designed a coreference module, instead of clustering algorithm or knowledge base search methods, to integrate with the enhanced coherence model. In addition, we fully merged coreference feature into similarity assessment of adjacent sentences, and the semantic coherence. Experiments show that our model outperforms entity-based model and LSA methods and has an ideal effect on students' essay automatic assessment.
AB - Many attempts on improving entity grid model have been made and boost the research on text coherence. However, only a few of them applied it to noisy data domain and students' essay. Thus, we proposed a novel discourse coherence model, which is based on entity grid model, to evaluate coherence on Chinese students' essay. In allusion to the feature of Chinese students' essay, frequently using lexical repetition and coreference methods in coherence essay, we designed a coreference module, instead of clustering algorithm or knowledge base search methods, to integrate with the enhanced coherence model. In addition, we fully merged coreference feature into similarity assessment of adjacent sentences, and the semantic coherence. Experiments show that our model outperforms entity-based model and LSA methods and has an ideal effect on students' essay automatic assessment.
KW - Chinese Students' Essay
KW - Coreference Module
KW - Discourse Coherence Model
KW - Entity Chain Grid
UR - http://www.scopus.com/inward/record.url?scp=85048207200&partnerID=8YFLogxK
U2 - 10.1109/PIC.2017.8359586
DO - 10.1109/PIC.2017.8359586
M3 - Conference Proceeding
AN - SCOPUS:85048207200
T3 - Proceedings of 2017 International Conference on Progress in Informatics and Computing, PIC 2017
SP - 430
EP - 434
BT - Proceedings of 2017 International Conference on Progress in Informatics and Computing, PIC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Progress in Informatics and Computing, PIC 2017
Y2 - 15 December 2017 through 17 December 2017
ER -