{"title":"提出了在web数据流中查找频繁项集的方法","authors":"Farzaneh Kaviani, M. Khayyambashi","doi":"10.5899/2016/JSCA-00065","DOIUrl":null,"url":null,"abstract":"Continual data checking is considered as one of the most common search tools for frequent itemsets which requires storage on memory. On the other hand, according to properties of data stream which are unlimited productions with a high-speed, it is not possible saving these data on memory and we need for techniques which enables online processing and finding repetitive standards. One of the most popular techniques in this case is using sliding windows. The benefits of these windows can be reducing memory usage and also search acceleration. In this article, a new vertical display and an algorithm is provided based on the pins in order to find frequent itemsets in data streams. Since this new display has a compressed format itself so, the proposed algorithm in terms of memory consumption and processing is more efficient than any other similar algorithms.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"46 1","pages":"28-34"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Method presented for finding Frequent Itemsets in web data streams\",\"authors\":\"Farzaneh Kaviani, M. Khayyambashi\",\"doi\":\"10.5899/2016/JSCA-00065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Continual data checking is considered as one of the most common search tools for frequent itemsets which requires storage on memory. On the other hand, according to properties of data stream which are unlimited productions with a high-speed, it is not possible saving these data on memory and we need for techniques which enables online processing and finding repetitive standards. One of the most popular techniques in this case is using sliding windows. The benefits of these windows can be reducing memory usage and also search acceleration. In this article, a new vertical display and an algorithm is provided based on the pins in order to find frequent itemsets in data streams. Since this new display has a compressed format itself so, the proposed algorithm in terms of memory consumption and processing is more efficient than any other similar algorithms.\",\"PeriodicalId\":38638,\"journal\":{\"name\":\"International Journal of Advances in Soft Computing and its Applications\",\"volume\":\"46 1\",\"pages\":\"28-34\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Advances in Soft Computing and its Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5899/2016/JSCA-00065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advances in Soft Computing and its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5899/2016/JSCA-00065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Method presented for finding Frequent Itemsets in web data streams
Continual data checking is considered as one of the most common search tools for frequent itemsets which requires storage on memory. On the other hand, according to properties of data stream which are unlimited productions with a high-speed, it is not possible saving these data on memory and we need for techniques which enables online processing and finding repetitive standards. One of the most popular techniques in this case is using sliding windows. The benefits of these windows can be reducing memory usage and also search acceleration. In this article, a new vertical display and an algorithm is provided based on the pins in order to find frequent itemsets in data streams. Since this new display has a compressed format itself so, the proposed algorithm in terms of memory consumption and processing is more efficient than any other similar algorithms.
期刊介绍：
The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.
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