Constructing And Mining Web-Scale Knowledge Graphs

IR(2016)

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摘要
Recent years have witnessed a proliferation of large-scale knowledge graphs, from purely academic projects such as YAGO to major commercial projects such as Google's Knowledge Graph and Microsoft's Satori. Whereas there is a large body of research on mining homogeneous graphs, this new generation of information networks are highly heterogeneous, with thousands of entity and relation types and billions of instances of those types (graph vertices and edges). In this tutorial, we present the state of the art in constructing, mining, and growing knowledge graphs. The purpose of the tutorial is to equip newcomers to this exciting field with an understanding of the basic concepts, tools and methodologies, open research challenges, as well as pointers to available datasets and relevant literature. Knowledge graphs have become an enabling resource for a plethora of new knowledge-rich applications. Consequently, the tutorial will also discuss the role of knowledge bases in empowering a range of web applications, from web search to social networks to digital assistants. A publicly available knowledge base (Freebase) will be used throughout the tutorial to exemplify the different techniques.
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