TY - JOUR
T1 - Predicting simplified thematic progression pattern for discourse analysis
AU - Xi, Xuefeng
AU - Sheng, Victor S.
AU - Yang, Shuhui
AU - Fu, Baochuan
AU - Cui, Zhiming
N1 - Publisher Copyright:
© 2020 Tech Science Press. All rights reserved.
PY - 2020/3/3
Y1 - 2020/3/3
N2 - The pattern of thematic progression, reflecting the semantic relationships between contextual two sentences, is an important subject in discourse analysis. We introduce a new corpus of Chinese news discourses annotated with thematic progression information and explore some computational methods to automatically extracting the discourse structural features of simplified thematic progression pattern (STPP) between contextual sentences in a text. Furthermore, these features are used in a hybrid approach to a major discourse analysis task, Chinese coreference resolution. This novel approach is built up via heuristic sieves and a machine learning method that comprehensively utilizes both the top-down STPP features and the bottom-up semantic features. Experimental results on the intersection of the CoNLL-2012 task shared dataset and the CDTC corpus demonstrate the effectiveness of our proposed approach.
AB - The pattern of thematic progression, reflecting the semantic relationships between contextual two sentences, is an important subject in discourse analysis. We introduce a new corpus of Chinese news discourses annotated with thematic progression information and explore some computational methods to automatically extracting the discourse structural features of simplified thematic progression pattern (STPP) between contextual sentences in a text. Furthermore, these features are used in a hybrid approach to a major discourse analysis task, Chinese coreference resolution. This novel approach is built up via heuristic sieves and a machine learning method that comprehensively utilizes both the top-down STPP features and the bottom-up semantic features. Experimental results on the intersection of the CoNLL-2012 task shared dataset and the CDTC corpus demonstrate the effectiveness of our proposed approach.
KW - Discourse topic
KW - Thematic progression
KW - Theme-rheme theory
UR - http://www.scopus.com/inward/record.url?scp=85085605176&partnerID=8YFLogxK
U2 - 10.32604/cmc.2020.06992
DO - 10.32604/cmc.2020.06992
M3 - Article
AN - SCOPUS:85085605176
SN - 1546-2218
VL - 63
SP - 163
EP - 181
JO - Computers, Materials and Continua
JF - Computers, Materials and Continua
IS - 1
ER -