{"title":"商业智能探索者与传统探索者的比较研究","authors":"Zhaohui Yu, Xiang Ji","doi":"10.1109/BMEI.2010.5639833","DOIUrl":null,"url":null,"abstract":"Business Intelligence Explorer uses a new browsing method and the framework incorporates visualization, web mining and clustering techniques to support effective exploration of knowledge. To examine whether the business intelligence explorer did optimize the search result or not, this paper chose three research objects, Google, Quintura, Clusty, and conducted an analysis of variance in terms of efficiency, effectiveness and usability. The result shows that visualization and clustering techniques offers practical implications for search engine users.","PeriodicalId":231601,"journal":{"name":"2010 3rd International Conference on Biomedical Engineering and Informatics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The comparative study of the Business Intelligence Explorer and the traditional explorer\",\"authors\":\"Zhaohui Yu, Xiang Ji\",\"doi\":\"10.1109/BMEI.2010.5639833\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Business Intelligence Explorer uses a new browsing method and the framework incorporates visualization, web mining and clustering techniques to support effective exploration of knowledge. To examine whether the business intelligence explorer did optimize the search result or not, this paper chose three research objects, Google, Quintura, Clusty, and conducted an analysis of variance in terms of efficiency, effectiveness and usability. The result shows that visualization and clustering techniques offers practical implications for search engine users.\",\"PeriodicalId\":231601,\"journal\":{\"name\":\"2010 3rd International Conference on Biomedical Engineering and Informatics\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 3rd International Conference on Biomedical Engineering and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BMEI.2010.5639833\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 3rd International Conference on Biomedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2010.5639833","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The comparative study of the Business Intelligence Explorer and the traditional explorer
Business Intelligence Explorer uses a new browsing method and the framework incorporates visualization, web mining and clustering techniques to support effective exploration of knowledge. To examine whether the business intelligence explorer did optimize the search result or not, this paper chose three research objects, Google, Quintura, Clusty, and conducted an analysis of variance in terms of efficiency, effectiveness and usability. The result shows that visualization and clustering techniques offers practical implications for search engine users.
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