{"title":"微博动态主题挖掘融合了用户行为和时间窗口","authors":"Fei Wu, Zhuo Wang, Zhengtao Yu, Liren Wang, Feng Zhou","doi":"10.1109/IALP.2017.8300535","DOIUrl":null,"url":null,"abstract":"Compared with traditional text, microblog text has features of user behavior and time window. Catered to features of microblog text, this paper proposed a method of dynamic topic mining for Microblog fused with user behavior and time window. Based on traditional LDA model, we use method of time window division to divide microblog text into each time window, then fuse features of user behavior in our model as guide information, sequentially construct dynamic topic mining for Microblog fused with user behavior and time window. Result of the experiment shows that the model we proposed has better effect on topic in microblog analyzing and topic intensity changing with time.","PeriodicalId":183586,"journal":{"name":"2017 International Conference on Asian Language Processing (IALP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Dynamic topic mining for microblog fused with user's behavior and time window\",\"authors\":\"Fei Wu, Zhuo Wang, Zhengtao Yu, Liren Wang, Feng Zhou\",\"doi\":\"10.1109/IALP.2017.8300535\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compared with traditional text, microblog text has features of user behavior and time window. Catered to features of microblog text, this paper proposed a method of dynamic topic mining for Microblog fused with user behavior and time window. Based on traditional LDA model, we use method of time window division to divide microblog text into each time window, then fuse features of user behavior in our model as guide information, sequentially construct dynamic topic mining for Microblog fused with user behavior and time window. Result of the experiment shows that the model we proposed has better effect on topic in microblog analyzing and topic intensity changing with time.\",\"PeriodicalId\":183586,\"journal\":{\"name\":\"2017 International Conference on Asian Language Processing (IALP)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Asian Language Processing (IALP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IALP.2017.8300535\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Asian Language Processing (IALP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IALP.2017.8300535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic topic mining for microblog fused with user's behavior and time window
Compared with traditional text, microblog text has features of user behavior and time window. Catered to features of microblog text, this paper proposed a method of dynamic topic mining for Microblog fused with user behavior and time window. Based on traditional LDA model, we use method of time window division to divide microblog text into each time window, then fuse features of user behavior in our model as guide information, sequentially construct dynamic topic mining for Microblog fused with user behavior and time window. Result of the experiment shows that the model we proposed has better effect on topic in microblog analyzing and topic intensity changing with time.