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What Makes a Phone a Business Phone - Querying Concepts in Product Data

机译:是什么让电话成为商务电话-查询产品数据中的概念

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The Web has become the primary source of information containing both structured and unstructured information. A good example is e-commerce where products are usually described by technical specifications (structured data) and textual user reviews (unstructured data). Both sources of information complement each other, covering quantifiable as well as perceived aspects of each product. In fact, for most searches users will have more or less abstract concepts in mind, as opposed to clear cut categorical information. In this paper we develop a novel approach to reveal implicit product features for querying by combining structured product data with natural-language product reviews. Using a self-supervised learning technique we progressively build a query-aware representation of the product domain under consideration. This representation can then effectively be used for intuitive querying. We performed extensive experiments confirming the effectiveness of our approach over real world product data. In particular, our evaluations show vastly improved precision and recall over the respective IR techniques.
机译:Web已成为包含结构化和非结构化信息的主要信息来源。一个很好的例子是电子商务,其中通常通过技术规格(结构化数据)和文本用户评论(非结构化数据)来描述产品。两种信息来源都是相辅相成的,涵盖了每种产品的可量化以及可感知的方面。实际上,对于大多数搜索,用户将或多或少地记住抽象概念,这与清晰的分类信息相反。在本文中,我们开发了一种新颖的方法,通过结合结构化产品数据和自然语言产品评论来揭示隐式产品特征以进行查询。使用自我监督的学习技术,我们逐步构建了所考虑产品域的查询感知表示形式。然后,可以将该表示有效地用于直观查询。我们进行了广泛的实验,证实了我们的方法对实际产品数据的有效性。特别是,我们的评估结果显示,与相应的IR技术相比,其准确性和召回率大大提高。

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