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Pattern Mining for General Intelligence: The FISHGRAM Algorithm for Frequent and Interesting Subhypergraph Mining

  • Jade O’Neill
  • Ben Goertzel
  • Shujing Ke
  • Ruiting Lian
  • Keyvan Sadeghi
  • Simon Shiu
  • Dingjie Wang
  • Gino Yu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7716)

Abstract

Fishgram, a novel algorithm for recognizing frequent or otherwise interesting sub-hypergraphs in large, heterogeneous hypergraphs, is presented. The algorithm’s implementation the OpenCog integrative AGI framework is described, and concrete examples are given showing the patterns it recognizes in OpenCog’s hypergraph knowledge store when the OpenCog system is used to control a virtual agent in a game world. It is argued that Fishgram is well suited to fill a critical niche in OpenCog and potentially other integrative AGI architectures: scalable recognition of relatively simple patterns in heterogeneous, potentially rapidly-changing data.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jade O’Neill
    • 1
  • Ben Goertzel
    • 2
    • 3
    • 4
  • Shujing Ke
    • 1
    • 2
    • 4
  • Ruiting Lian
    • 2
    • 4
  • Keyvan Sadeghi
    • 2
  • Simon Shiu
    • 1
  • Dingjie Wang
    • 2
    • 4
  • Gino Yu
    • 2
  1. 1.Dept. of Computer ScienceHong Kong Poly UHong Kong
  2. 2.School of DesignHong Kong Poly UHong Kong
  3. 3.Novamente LLCUSA
  4. 4.Dept. of Cognitive ScienceXiamen UniversityChina

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