Paper Info
Title
Constructing and Mining Web-scale Knowledge Graphs.
Abstract
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.
Year
DOI
Venue
2016
10.1145/2911451.2914807
SIGIR
Field
DocType
Citations 
Data science,Open research,Pointer (computer programming),Data mining,Graph,World Wide Web,Knowledge graph,Social network,Computer science,Knowledge extraction,Web application,Knowledge base
Conference
3
PageRank 
References 
Authors
0.39
14
2
Name
Order
Citations
PageRank
Evgeniy Gabrilovich14573224.48
Nicolas Usunier2197497.52