{"title":"使用情感本体识别电子邮件中的冲突","authors":"Chahnez Zakaria, Olivier Curé, K. Smaïli","doi":"10.5220/0002172000460054","DOIUrl":null,"url":null,"abstract":"In the logic of text classification, this paper presents an approach to detect emails conflict exchanged between colleagues, who belong to a geographically distributed enterprise. The idea is to inform a team leader of such situation, hence to help him in preventing serious disagreement between team members. This approach uses the vector space model with TF*IDF weight to represent email; and a domain ontology of relational conflicts to determine its categories. Our study also addresses the issue of building ontology, which is made up of two phases. First we conceptualize the domain by hand, then we enrich it by using the triggers model that enables to find out terms in corpora which correspond to different conflicts.","PeriodicalId":378427,"journal":{"name":"International Workshop on Natural Language Processing and Cognitive Science","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying Conflicts through eMails by using an Emotion Ontology\",\"authors\":\"Chahnez Zakaria, Olivier Curé, K. Smaïli\",\"doi\":\"10.5220/0002172000460054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the logic of text classification, this paper presents an approach to detect emails conflict exchanged between colleagues, who belong to a geographically distributed enterprise. The idea is to inform a team leader of such situation, hence to help him in preventing serious disagreement between team members. This approach uses the vector space model with TF*IDF weight to represent email; and a domain ontology of relational conflicts to determine its categories. Our study also addresses the issue of building ontology, which is made up of two phases. First we conceptualize the domain by hand, then we enrich it by using the triggers model that enables to find out terms in corpora which correspond to different conflicts.\",\"PeriodicalId\":378427,\"journal\":{\"name\":\"International Workshop on Natural Language Processing and Cognitive Science\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Natural Language Processing and Cognitive Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0002172000460054\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Natural Language Processing and Cognitive Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0002172000460054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying Conflicts through eMails by using an Emotion Ontology
In the logic of text classification, this paper presents an approach to detect emails conflict exchanged between colleagues, who belong to a geographically distributed enterprise. The idea is to inform a team leader of such situation, hence to help him in preventing serious disagreement between team members. This approach uses the vector space model with TF*IDF weight to represent email; and a domain ontology of relational conflicts to determine its categories. Our study also addresses the issue of building ontology, which is made up of two phases. First we conceptualize the domain by hand, then we enrich it by using the triggers model that enables to find out terms in corpora which correspond to different conflicts.