Xuefeng Xi1, Victor S. Sheng1, 2, *, Shuhui Yang3, Baochuan Fu1, Zhiming Cui1
CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 163-181, 2020, DOI:10.32604/cmc.2020.06992
Abstract 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… More >
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