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On Relaxing Contextual Preference Queries

机译:关于放宽上下文首选项查询

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摘要

Personalization systems exploit preferences for providing users with only relevant data from the huge volume of information that is currently available. We consider preferences that dependent on context, such as the location of the user. We model context as a set of attributes, each taking values from hierarchical domains. Often, the context of the query may be too specific to match any of the given preferences. In this paper, we consider possible expansions of the query context produced by relaxing one or more of its context attributes. A hierarchical attribute may be relaxed upwards by replacing its value by a more general one, downwards by replacing its value by a set of more specific values or sideways by replacing its value by sibling values in the hierarchy. We present an algorithm based on a prefix-based representation of context for identifying the preferences whose context matches the relaxed context of the query and some initial performance results.
机译:个性化系统利用首选项为用户提供当前可用的大量信息中的仅相关数据。我们考虑依赖于上下文的首选项,例如用户的位置。我们将上下文建模为一组属性,每个属性都从层次结构域中获取值。通常,查询的上下文可能太具体而无法匹配任何给定的首选项。在本文中,我们考虑了通过放宽其一个或多个上下文属性而产生的查询上下文的可能扩展。可以通过用更通用的属性替换其值来向上放宽分层属性,通过用一组更具体的值替换其值来向下放宽,或者通过在层次结构中同级值替换其值来向侧面放宽。我们提出了一种基于上下文的基于前缀的表示的算法,用于识别其上下文与查询的宽松上下文和一些初始性能结果相匹配的首选项。

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