志愿者数据仓库:最新技术

IF 0.5 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Amir Sakka, S. Bimonte, F. Pinet, Lucile Sautot
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引用次数: 1

摘要

随着众包系统的成熟,新的分析可能性出现,志愿者通过将实践和日常经验中产生的隐性知识发挥关键作用。同时,数据仓库和OLAP系统代表了决策支持系统的第一个公民。它们允许根据多维模型分析大量数据。多维模型越能反映决策者的分析需求,DW项目就越成功。然而,当志愿者参与DW的设计时,现有的DW设计方法存在一些局限性。在这项工作中,作者介绍了志愿数据仓库(VDW)设计的主要特征,并研究了现有的主要数据仓库设计方法,以找出他们如何能够为实现这种特定数据仓库方法所需的特征做出贡献。为了提供一个对现有工作进行分类的正式框架,他们对经典DW用户和志愿者之间的差异进行了研究。本文还提出了一组VDW的开放问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Volunteer Data Warehouse: State of the Art
With the maturity of crowdsourcing systems, new analysis possibilities appear where volunteers play a crucial role by bringing the implicit knowledge issued from practical and daily experience. At the same time, data warehouse and OLAP systems represent the first citizen of decision-support systems. They allow analyzing a huge volume of data according to the multidimensional model. The more the multidimensional model reflects the decision-makers' analysis needs, the more the DW project is successful. However, when volunteers are involved in the design of DWs, existing DW design methodologies present some limitations. In this work, the authors present the main features of volunteer data warehouse (VDW) design, and they study the main existing DW design methodology to find out how they can contribute to fulfil the features needed by this particular DW approach. To provide a formal framework to classify existing work, they provide a study of differences between classical DW users and volunteers. The paper also presents a set of open issues for VDW.
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来源期刊
International Journal of Data Warehousing and Mining
International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.40
自引率
0.00%
发文量
20
审稿时长
>12 weeks
期刊介绍: 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
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