{"title":"基于主义位的知网汉语情感词库构建","authors":"Bin Liu, F. Ren, Cong Wang","doi":"10.1109/ICNC.2008.194","DOIUrl":null,"url":null,"abstract":"We propose a novel, convenient way for the building of emotion thesaurus which can be used in assessing the affective qualities of natural languages contained in text. Our main goals are fast analysis and visualization of affective content for machines to communicate smoothly with humans and to realize emotion communications. Although there have been some studies about analyzing affective content in text, our primary unique method is mainly according to the main sememe of HowNet which is an on-line common sense knowledge base unveiling inter-conceptual relations and inter-attribute relations of concepts as connoting in lexicons of the Chinese and their English equivalents. Therefore our processing of the affective content is lead into the semantic level.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"47 1","pages":"91-95"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Building of Chinese Emotion Thesaurus Using HowNet Based on the Main Sememe\",\"authors\":\"Bin Liu, F. Ren, Cong Wang\",\"doi\":\"10.1109/ICNC.2008.194\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel, convenient way for the building of emotion thesaurus which can be used in assessing the affective qualities of natural languages contained in text. Our main goals are fast analysis and visualization of affective content for machines to communicate smoothly with humans and to realize emotion communications. Although there have been some studies about analyzing affective content in text, our primary unique method is mainly according to the main sememe of HowNet which is an on-line common sense knowledge base unveiling inter-conceptual relations and inter-attribute relations of concepts as connoting in lexicons of the Chinese and their English equivalents. Therefore our processing of the affective content is lead into the semantic level.\",\"PeriodicalId\":6404,\"journal\":{\"name\":\"2008 Fourth International Conference on Natural Computation\",\"volume\":\"47 1\",\"pages\":\"91-95\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Fourth International Conference on Natural Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2008.194\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Fourth International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2008.194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Building of Chinese Emotion Thesaurus Using HowNet Based on the Main Sememe
We propose a novel, convenient way for the building of emotion thesaurus which can be used in assessing the affective qualities of natural languages contained in text. Our main goals are fast analysis and visualization of affective content for machines to communicate smoothly with humans and to realize emotion communications. Although there have been some studies about analyzing affective content in text, our primary unique method is mainly according to the main sememe of HowNet which is an on-line common sense knowledge base unveiling inter-conceptual relations and inter-attribute relations of concepts as connoting in lexicons of the Chinese and their English equivalents. Therefore our processing of the affective content is lead into the semantic level.