知识图探索的图查询建议

Matteo Lissandrini, D. Mottin, Themis Palpanas, Yannis Velegrakis
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引用次数: 25

摘要

我们考虑了在知识图上通过图查询进行探索性搜索的任务。我们建议通过使用直观的建议扩展查询来帮助用户,以提供更有信息的(完整的)查询,可以检索更详细和相关的答案。为了实现这一结果,我们提出了一个模型,该模型可以将图搜索范式与成熟的信息检索技术连接起来。我们的方法不需要用户提供任何额外的知识,而是建立在有原则的语言建模方法之上。我们通过经验展示了我们的方法在大型知识图谱上的有效性和效率,以及我们的建议如何能够帮助构建更完整和信息丰富的查询。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graph-Query Suggestions for Knowledge Graph Exploration
We consider the task of exploratory search through graph queries on knowledge graphs. We propose to assist the user by expanding the query with intuitive suggestions to provide a more informative (full) query that can retrieve more detailed and relevant answers. To achieve this result, we propose a model that can bridge graph search paradigms with well-established techniques for information-retrieval. Our approach does not require any additional knowledge from the user and builds on principled language modelling approaches. We empirically show the effectiveness and efficiency of our approach on a large knowledge graph and how our suggestions are able to help build more complete and informative queries.
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