{"title":"词义猜测:基于知识图谱的方法","authors":"Yiming Wei, Zhi-Yong Peng, Tan Dai","doi":"10.1109/BESC48373.2019.8963023","DOIUrl":null,"url":null,"abstract":"In order to tackle issues of traditional corpus, such as low updating rate, we propose a novel corpus based on Knowledge Graph. In this paper we do experiments that are particularly designed to use one specific sense guessing model. This paper also compares the results of experiments which are respectively based on traditional and novel ones.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Word Sense Guessing: A Knowledge Graph based Approach\",\"authors\":\"Yiming Wei, Zhi-Yong Peng, Tan Dai\",\"doi\":\"10.1109/BESC48373.2019.8963023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to tackle issues of traditional corpus, such as low updating rate, we propose a novel corpus based on Knowledge Graph. In this paper we do experiments that are particularly designed to use one specific sense guessing model. This paper also compares the results of experiments which are respectively based on traditional and novel ones.\",\"PeriodicalId\":190867,\"journal\":{\"name\":\"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BESC48373.2019.8963023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BESC48373.2019.8963023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Word Sense Guessing: A Knowledge Graph based Approach
In order to tackle issues of traditional corpus, such as low updating rate, we propose a novel corpus based on Knowledge Graph. In this paper we do experiments that are particularly designed to use one specific sense guessing model. This paper also compares the results of experiments which are respectively based on traditional and novel ones.