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TB-Structure: Collective Intelligence for Exploratory Keyword Search

机译:TB结构:探索性关键字搜索的集体智慧

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In this paper we address an exploratory search challenge by presenting a new (structure-driven) collaborative filtering technique. The aim is to increase search effectiveness by predicting implicit seeker's intents at an early stage of the search process. This is achieved by uncovering behavioral patterns within large datasets of preserved collective search experience. We apply a specific tree-based data structure called a TB (There-and-Back) structure for compact storage of search history in the form of merged query trails - sequences of queries approaching iteratively a seeker's goal. The organization of TB-structures allows inferring new implicit trails for the prediction of a seeker's intents. We used experiments to demonstrate both: the storage compactness and inference potential of the proposed structure.
机译:在本文中,我们通过提出一种新的(结构驱动)协作过滤技术来解决探索性搜索难题。目的是通过在搜索过程的早期阶段预测隐式搜索者的意图来提高搜索效率。这是通过在保留的集体搜索体验的大型数据集中发现行为模式来实现的。我们将特定的基于树的数据结构称为TB(即回)结构,以合并的查询线索的形式紧凑地存储搜索历史记录-迭代地接近搜索者目标的查询序列。结核病结构的组织可以推断出新的隐含踪迹,以预测寻求者的意图。我们使用实验来证明:所提出结构的存储紧凑性和推断潜力。

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