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Knowledge Exploration Using Tables on the Web

机译:使用网络表进行知识探索

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The increasing popularity of mobile device usage has ushered in many features in modern search engines that help users with various information needs. One of those needs is Knowledge Exploration, where related documents are returned in response to a user query, either directly through right-hand side knowledge panels or indirectly through navigable sections underneath individual search results. Existing knowledge exploration features have relied on a combination of Knowledge Bases and query logs. In this paper, we propose Knowledge Carousels of two modalities, namely sideways and downwards, that facilitate exploration of IS-A and HAS-A relationships, respectively, with regard to an entity-seeking query, based on leveraging the large corpus of tables on the Web. This brings many technical challenges, including associating correct carousels with the search entity, selecting the best carousel from the candidates, and finding titles that best describe the carousel. We describe how we address these challenges and also experimentally demonstrate through user studies that our approach produces better result sets than baseline approaches.
机译:移动设备使用的日益普及已经在现代搜索引擎中引入了许多功能,这些功能可以帮助用户满足各种信息需求。这些需求之一是Knowledge Exploration,其中直接通过右侧知识面板或通过单独搜索结果下方的可导航部分间接返回相关文档以响应用户查询。现有的知识探索功能依赖于知识库和查询日志的组合。在本文中,我们提出了两种形式的知识轮播,即侧向和向下,分别利用实体上的大量语料库,有助于探索IS-A和HAS-A关系,以寻求实体查询。网络。这带来了许多技术挑战,包括将正确的轮播与搜索实体相关联,从候选者中选择最佳轮播以及找到最能描述轮播的标题。我们描述了如何应对这些挑战,并通过用户研究实验证明了我们的方法比基线方法能产生更好的结果集。

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