评估和选择Web源作为数据仓库的外部信息资源

Yan Zhu, A. Buchmann
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引用次数: 59

摘要

一个公司的本地数据往往不足以分析市场趋势和制定合理的商业计划。决策还必须基于来自供应商、合作伙伴和竞争对手的信息。系统地将来自Web的适当外部数据集成到数据仓库中是一种有意义的解决方案,将使企业受益。然而,Web的自主性和动态性使得从Web中选择相关和合格的外部数据的任务具有挑战性。我们开发了一组用于评估和选择Web资源作为数据仓库的外部数据源的标准,并讨论了如何使用多标准决策(MCDM)方法筛选Web数据源。关于选择Web源的最终决定对关键因素很敏感,即,根据每个标准的标准权重和备选方案的性能分数。我们根据关键因素分析了备选方案最终排名的敏感性,以便深入了解我们最终决策的稳定性。本文还比较了几种用于Web源筛选的MCDM方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating and selecting Web sources as external information resources of a data warehouse
A company's local data is often insufficient for analyzing market trends and making reasonable business plans. Decision making must also be based on information from suppliers, partners and competitors. Systematically integrating suitable external data from the Web into a data warehouse is a meaningful solution and will benefit the enterprise. However, the autonomy and dynamics of the Web make the task of selecting relevant and qualified external data from the Web challenging. We develop a set of criteria for evaluating and selecting Web resources as external data sources of a data warehouse and discuss how to screen Web data sources using multi-criteria decision making (MCDM) methods. The final decision with respect to selecting Web sources is sensitive to critical factors, i.e., the criterion weight and performance score of alternatives in terms of each criterion. We analyzed the sensitivity of the final rank of alternatives in terms of critical factors in order to gain an insight into the stability of our final decision. The comparison of several MCDM approaches for Web source screening is also presented.
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