{"title":"基于张量子空间模型的多维数据流分析并行算法","authors":"B. Cyganek","doi":"10.1109/HPCS.2018.00139","DOIUrl":null,"url":null,"abstract":"In this paper the parallel models for processing of the multi-dimensional data streams are discussed. Stream analysis is performed by tensor models and a fitness measure. The method was tested on the problem of video shot detection showing good accuracy. In this paper efficient algorithms for tensor model construction and model update in the parallel processing framework are presented. Also the parallel version for the off-line stream processing is proposed.","PeriodicalId":308138,"journal":{"name":"2018 International Conference on High Performance Computing & Simulation (HPCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Parallel Algorithms for Multidimensional Data Streams Analysis with Tensor Subspace Models\",\"authors\":\"B. Cyganek\",\"doi\":\"10.1109/HPCS.2018.00139\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the parallel models for processing of the multi-dimensional data streams are discussed. Stream analysis is performed by tensor models and a fitness measure. The method was tested on the problem of video shot detection showing good accuracy. In this paper efficient algorithms for tensor model construction and model update in the parallel processing framework are presented. Also the parallel version for the off-line stream processing is proposed.\",\"PeriodicalId\":308138,\"journal\":{\"name\":\"2018 International Conference on High Performance Computing & Simulation (HPCS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on High Performance Computing & Simulation (HPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCS.2018.00139\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCS.2018.00139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel Algorithms for Multidimensional Data Streams Analysis with Tensor Subspace Models
In this paper the parallel models for processing of the multi-dimensional data streams are discussed. Stream analysis is performed by tensor models and a fitness measure. The method was tested on the problem of video shot detection showing good accuracy. In this paper efficient algorithms for tensor model construction and model update in the parallel processing framework are presented. Also the parallel version for the off-line stream processing is proposed.