Summarizing Conceptual Graphs for Automatic Summarization Task

  • Sabino Miranda-Jiménez
  • Alexander Gelbukh
  • Grigori Sidorov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7735)


We propose a conceptual graph-based framework for abstractive text summarization. While syntactic or partial semantic representations of texts have been used in literature, complete semantic representations have not been explored for this purpose. We use a complete semantic representation, namely, conceptual graph structures, composed of concepts and conceptual relations. To summarize a conceptual graph, we remove the nodes that represent less important content, and apply certain operations on the resulting smaller conceptual graphs. We measure the importance of nodes on weighted conceptual graphs by the HITS algorithm, augmented with some heuristics based on VerbNet semantic patterns. Our experimental results are promising.


Automatic summarization conceptual graphs graph-based ranking algorithms HITS algorithm 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sabino Miranda-Jiménez
    • 1
  • Alexander Gelbukh
    • 1
  • Grigori Sidorov
    • 1
  1. 1.Natural Language and Text Processing Laboratory, Center for Computing ResearchNational Polytechnic InstituteMexico CityMexico

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