Research Article
Construction of Unsupervised Prose Text Emotional Lexicon Based on Multidimensional Fusion
@INPROCEEDINGS{10.1007/978-3-030-77428-8_11, author={Kai Zhang and Jianshe Zhou and Su Dong}, title={Construction of Unsupervised Prose Text Emotional Lexicon Based on Multidimensional Fusion}, proceedings={Tools for Design, Implementation and Verification of Emerging Information Technologies. 15th EAI International Conference, TridentCom 2020, Virtual Event, November 13, 2020, Proceedings}, proceedings_a={TRIDENTCOM}, year={2021}, month={5}, keywords={Prose emotional lexicon Prose reading comprehension Random walk Word vector Word co-occurrence}, doi={10.1007/978-3-030-77428-8_11} }- Kai Zhang
Jianshe Zhou
Su Dong
Year: 2021
Construction of Unsupervised Prose Text Emotional Lexicon Based on Multidimensional Fusion
TRIDENTCOM
Springer
DOI: 10.1007/978-3-030-77428-8_11
Abstract
Affective computing is an important tool for language processing and opinion mining, and emotional lexicon is the basis of emotional computing, and prose accounts for a large proportion in Chinese teaching and application in China. The construction of special emotional lexicon for prose language learning and language understanding is of great significance to the development of machine assisted human language learning and the improvement of machine deep reading comprehension. Therefore, the research on the construction of prose emotional lexicon is of great significance and value. In this paper, with the help of data collection tools, more than 27000 pieces of modern famous prose database are constructed. After preprocessing the data, denoising, deleting and selecting are completed to determine the walk set. Compared with PMI and word2vec, the accuracy of the method is improved by 16% and 14.8%, which proves that the comprehensive vector space can effectively improve the emotional vocabulary recognition of prose. Finally, 12762 prose general emotional lexicon is formed with the help of this method.
