{"title":"基于语言摘要的交互式数据探索","authors":"Grégory Smits, R. Yager, O. Pivert","doi":"10.1109/FUZZ-IEEE.2017.8015391","DOIUrl":null,"url":null,"abstract":"Extracting useful and interpretable knowledge from raw data is a crucial issue that has been largely addressed by the data mining community especially. In this paper we provide an interactive data exploration approach that relies on two steps. First, a personalized linguistic summary of the data set concerned is built and displayed as a tag cloud. Then, exploration functionalities are provided on top of the summary to let the user discover interesting properties in the data as frequent/atypical/diversified associations between properties.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Interactive data exploration on top of linguistic summaries\",\"authors\":\"Grégory Smits, R. Yager, O. Pivert\",\"doi\":\"10.1109/FUZZ-IEEE.2017.8015391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Extracting useful and interpretable knowledge from raw data is a crucial issue that has been largely addressed by the data mining community especially. In this paper we provide an interactive data exploration approach that relies on two steps. First, a personalized linguistic summary of the data set concerned is built and displayed as a tag cloud. Then, exploration functionalities are provided on top of the summary to let the user discover interesting properties in the data as frequent/atypical/diversified associations between properties.\",\"PeriodicalId\":408343,\"journal\":{\"name\":\"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZ-IEEE.2017.8015391\",\"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 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interactive data exploration on top of linguistic summaries
Extracting useful and interpretable knowledge from raw data is a crucial issue that has been largely addressed by the data mining community especially. In this paper we provide an interactive data exploration approach that relies on two steps. First, a personalized linguistic summary of the data set concerned is built and displayed as a tag cloud. Then, exploration functionalities are provided on top of the summary to let the user discover interesting properties in the data as frequent/atypical/diversified associations between properties.
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