International Journal of Data Warehousing and Mining

International Journal of Data Warehousing and Mining期刊基本信息

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官方网站:http://www.igi-global.com/bookstore/titledetails.aspx?titleid=1085

投稿网址:http://www.igi-global.com/calls-for-papers/international-journal-data-warehousing-mining/1085

PMC链接:http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1548-3924%5BISSN%5D

International Journal of Data Warehousing and Mining中文简介

《国际数据仓库与挖掘杂志》(IJDWM)发布了数据管理和分析领域的最新国际研究成果。IJDWM为最先进的开发和研究提供了一个论坛,以及当前专注于数据仓库和数据挖掘领域集成的创新活动。强调现实问题的适用性,满足学术研究者和实践IT专业人士的需求,致力于发表有关数据仓库和数据挖掘的理论发展和实际应用的高质量论文。最初的研究论文、最新的评论和技术说明被邀请出版。该期刊接受提交与数据仓库和数据挖掘相关的任何工作的论文。特别关注的是从数据仓库挖掘数据的论文;数据库、数据仓库和数据挖掘的集成;以及挖掘和归档数据的整体方法。主题涵盖算法应用程序问题数据集市数据挖掘数据挖掘方法数据模型数据结构数据仓库数据仓库流程设计知识发现过程挖掘数据库在线分析过程实际问题工具和语言

International Journal of Data Warehousing and Mining英文简介

The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving data.Topics CoveredAlgorithmsApplications issuesData martData MiningData mining methodsData modelsData structuresData WarehousingData warehousing processDesignKnowledge discovery processMining databasesOnline analytical processPractical issuesTools and languages

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