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Constructing and mining web-scale knowledge graphs: KDD 2014 tutorial

Published:24 August 2014Publication History

ABSTRACT

Recent years have witnessed a proliferation of large-scale knowledge graphs, such as Freebase, YAGO, 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 vertices and edges. In this tutorial, we will 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, available datasets, and open research challenges. A publicly available knowledge base (Freebase) will be used throughout the tutorial to exemplify the different techniques.

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    • Published in

      cover image ACM Conferences
      KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining
      August 2014
      2028 pages
      ISBN:9781450329569
      DOI:10.1145/2623330

      Copyright © 2014 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 August 2014

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      • tutorial

      Acceptance Rates

      KDD '14 Paper Acceptance Rate151of1,036submissions,15%Overall Acceptance Rate1,133of8,635submissions,13%

      Upcoming Conference

      KDD '24

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