{"title":"基于贝叶斯网络的话题建议增强了社区问答中的标签推理","authors":"Gerel Tumenbayar, Hung-Yu kao","doi":"10.1109/TAAI.2016.7880110","DOIUrl":null,"url":null,"abstract":"Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work aims to find this general conditional relationship between topics by using Bayesian Network model and then use this model to suggest the reasonable topics for professionals to further study.","PeriodicalId":159858,"journal":{"name":"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Topic suggestion by Bayesian network enhanced tag inference in community question answering\",\"authors\":\"Gerel Tumenbayar, Hung-Yu kao\",\"doi\":\"10.1109/TAAI.2016.7880110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work aims to find this general conditional relationship between topics by using Bayesian Network model and then use this model to suggest the reasonable topics for professionals to further study.\",\"PeriodicalId\":159858,\"journal\":{\"name\":\"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAAI.2016.7880110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAAI.2016.7880110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Topic suggestion by Bayesian network enhanced tag inference in community question answering
Since Web 2.0 emerges, users became very active in attending Web forum and Q&A Community. For the community about technology, engineering and science, it is likely that most of the professionals follow the same general path to study specific knowledge and this path would be between topics from basic one to specific one or from topic about old technology to a topic about new technology. Our work aims to find this general conditional relationship between topics by using Bayesian Network model and then use this model to suggest the reasonable topics for professionals to further study.