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The Layer-Seeds Term Clustering Method: Enabling Proactive Situation-Aware Product Recommendations in E-Commerce Dialogues

机译:层种子术语聚类方法:在电子商务对话中启用主动的情境感知产品推荐

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摘要

In e-commerce it is often crucial to provide customers a large choice of relevant offers. Users, however, seldom provides complete and comprehensive descriptions of their desires, therefore user interfaces are needed that can generate automatically expanded queries to the product database and proactively enrich the ongoing dialogue with recommendations of suitable products. Automatic query expansion is mostly based on thesaurus and/or user profiles. In e-commerce applications, specific thesauri reflecting the webstore 's product categories are desirable. This work describes a method for the automatic construction of a thesaurus based on existing categories of documents. A clustering algorithm, the "Layer-Seeds method", is introduced, which facilitates the automatic generation of thesaurus reflecting the specific vocabulary occurring in a given collection of documents. The clustering works on terms extracted from the documents in a certain category and organizes them in a tree-like hierarchical structure—a thesaurus. The thesaurus is then employed for automatic query expansion in an e-commerce application in order to obtain better results for product searching. Experiments yield evidence that a significant increase of user satisfaction is achieved.
机译:在电子商务中,为客户提供大量相关优惠通常是至关重要的。但是,用户很少提供他们的需求的完整而全面的描述,因此需要用户界面,这些界面可以自动生成对产品数据库的扩展查询,并通过适当产品的建议来积极丰富正在进行的对话。自动查询扩展主要基于同义词库和/或用户配置文件。在电子商务应用程序中,需要反映网络商店产品类别的特定叙词表。这项工作描述了一种基于现有文档类别自动构建同义词库的方法。引入了一种聚类算法,即“ Layer-Seeds方法”,它有助于自动生成同义词库,以反映给定文档集中出现的特定词汇。聚类基于从某个类别的文档中提取的术语进行工作,并以树状分层结构(同义词库)将它们组织起来。然后,将同义词库用于电子商务应用程序中的自动查询扩展,以便获得更好的产品搜索结果。实验表明,用户满意度得到了显着提高。

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