{"title":"基于关联规则的k -均值聚类算法研究","authors":"Wang Jun, Ouyang Zheng-zheng","doi":"10.1109/CESCE.2010.26","DOIUrl":null,"url":null,"abstract":"With the continued expansion of network resources and the rapid change of old and new information, the traditional information retrieval is difficult to adapt to the need of management of mass electronic data. It is a very important aspect of how to locate the information you want conveniently and accurately and improve the efficiency of search engines.","PeriodicalId":6371,"journal":{"name":"2010 International Conference on Challenges in Environmental Science and Computer Engineering","volume":"134 1","pages":"285-286"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The Research of K-means Clustering Algorithm Based on Association Rules\",\"authors\":\"Wang Jun, Ouyang Zheng-zheng\",\"doi\":\"10.1109/CESCE.2010.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the continued expansion of network resources and the rapid change of old and new information, the traditional information retrieval is difficult to adapt to the need of management of mass electronic data. It is a very important aspect of how to locate the information you want conveniently and accurately and improve the efficiency of search engines.\",\"PeriodicalId\":6371,\"journal\":{\"name\":\"2010 International Conference on Challenges in Environmental Science and Computer Engineering\",\"volume\":\"134 1\",\"pages\":\"285-286\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Challenges in Environmental Science and Computer Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CESCE.2010.26\",\"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 International Conference on Challenges in Environmental Science and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CESCE.2010.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Research of K-means Clustering Algorithm Based on Association Rules
With the continued expansion of network resources and the rapid change of old and new information, the traditional information retrieval is difficult to adapt to the need of management of mass electronic data. It is a very important aspect of how to locate the information you want conveniently and accurately and improve the efficiency of search engines.
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