{"title":"斜面系统优化在数据聚类中的应用","authors":"M. Mozaffari, H. Abdy, S. Zahiri","doi":"10.1109/PRIA.2013.6528451","DOIUrl":null,"url":null,"abstract":"Data-mining is a branch of science which tends to extract a series of futures and some meaningful information from a huge database in proper time and cost. Clustering is one of the popular methods in this field. The purpose of clustering is to use a database and group together its items with similar characteristics. Application of clustering in many fields of science and engineering problems like Pattern recognition, data retrieval, bio-informatics, machine learning and the Internet cause to have significantly developed in the last decades. A rapid growth in the volume of information in databases revealed weakness of traditional methods like K-means in facing with huge data. In this paper a new clustering method based on the Inclined Planes system Optimization algorithm was proposed and evaluate on a series of standard datasets. Comparison study revealed a significant superiority over other similar clustering algorithms.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Application of inclined planes system optimization on data clustering\",\"authors\":\"M. Mozaffari, H. Abdy, S. Zahiri\",\"doi\":\"10.1109/PRIA.2013.6528451\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data-mining is a branch of science which tends to extract a series of futures and some meaningful information from a huge database in proper time and cost. Clustering is one of the popular methods in this field. The purpose of clustering is to use a database and group together its items with similar characteristics. Application of clustering in many fields of science and engineering problems like Pattern recognition, data retrieval, bio-informatics, machine learning and the Internet cause to have significantly developed in the last decades. A rapid growth in the volume of information in databases revealed weakness of traditional methods like K-means in facing with huge data. In this paper a new clustering method based on the Inclined Planes system Optimization algorithm was proposed and evaluate on a series of standard datasets. Comparison study revealed a significant superiority over other similar clustering algorithms.\",\"PeriodicalId\":370476,\"journal\":{\"name\":\"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRIA.2013.6528451\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRIA.2013.6528451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of inclined planes system optimization on data clustering
Data-mining is a branch of science which tends to extract a series of futures and some meaningful information from a huge database in proper time and cost. Clustering is one of the popular methods in this field. The purpose of clustering is to use a database and group together its items with similar characteristics. Application of clustering in many fields of science and engineering problems like Pattern recognition, data retrieval, bio-informatics, machine learning and the Internet cause to have significantly developed in the last decades. A rapid growth in the volume of information in databases revealed weakness of traditional methods like K-means in facing with huge data. In this paper a new clustering method based on the Inclined Planes system Optimization algorithm was proposed and evaluate on a series of standard datasets. Comparison study revealed a significant superiority over other similar clustering algorithms.