User driven multi-criteria source selection
User driven multi-criteria source selection
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DOI：
10.1016/j.ins.2017.11.019
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发表时间：
2018-03
期刊：
影响因子：
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通讯作者：
Edward Abel;J. Keane;N. Paton;A. Fernandes;Martin Koehler;Nikolaos Konstantinou;Julio César Cortés Ríos;Nurzety A. Azuan;S. Embury
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文献类型：
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作者：
Edward Abel;J. Keane;N. Paton;A. Fernandes;Martin Koehler;Nikolaos Konstantinou;Julio César Cortés Ríos;Nurzety A. Azuan;S. Embury
源选择是识别最能满足用户需求的可用数据源子集的问题。在本文中，我们提出了一个用户驱动的方法来源选择，旨在确定最适合的目的的来源。该方法采用决策支持方法来考虑用户的上下文，允许最终用户通过指定不同标准之间的相对重要性来调整他们的偏好，寻找与他/她的偏好一致的折衷解决方案。该方法是可扩展的，以纳入不同的标准，而不是从一个固定的集合，和解决方案可以使用一个子集的数据，从每个选定的来源，而不是要求，来源是在其整体使用或根本没有。该文件描述和激励的方法，提出了一种方法，建模用户的上下文，其收集的优化算法，探索空间的解决方案，并使用多个真实的世界数据集来比较和评估所得到的算法。实验表明，源选择的结果是如何产生的，是调谐到每个用户的喜好，无论是相对于整体加权效用，并通过忠实地表示用户的喜好内的结果，同时扩展到潜在的数千个来源。
Source selection is the problem of identifying a subset of available data sources that best meet a user’s needs. In this paper we propose a user-driven approach to source selection that seeks to identify sources that are most fit for purpose. The approach employs a decision support methodology to take account of a user’s context, to allow end users to tune their preferences by specifying the relative importance between different criteria, looking to find a trade-off solution aligned with his/her preferences. The approach is extensible to incorporate diverse criteria, not drawn from a fixed set, and solutions can use a subset of the data from each selected source, rather than require that sources are used in their entirety or not at all.The paper describes and motivates the approach, presenting a methodology for modelling a user’s context, and its collection of optimisation algorithms for exploring the space of solutions, and compares and evaluates the resulting algorithms using multiple real world data sets. The experiments show how source selection results are produced that are attuned to each user’s preferences, both with respect to overall weighted utility and through faithful representation of a user’s preferences within a result, while scaling to potentially thousands of sources.