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Integrating Structure in the Probabilistic Model for Information Retrieval

机译:集成结构在概率模型中的信息检索

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In databases or in the World Wide Web, many documents are in a structured format (e.g. XML). We propose in this article to extend the classical IR probabilistic model in order to take into account the structure through the weighting of tags. Our approach includes a learning step in which the weight of each tag is computed. This weight estimates the probability that the tag distinguishes the terms which are the most relevant. Our model has been evaluated on a large collection during INEX IR evaluation campaigns.
机译:在数据库或全球网络中,许多文档都处于结构化格式(例如XML)。我们在本文中提出延长经典的IR概率模型,以便通过标签的加权来考虑结构。我们的方法包括一个学习步骤,其中计算了每个标签的权重。此权重估计标签区分最相关的术语的概率。我们的模型已经在Inex IR评估活动期间在大型集合中进行了评估。

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