Summarizing conceptual graphs for automatic summarization task

Sabino Miranda-Jiménez, Alexander Gelbukh, Grigori Sidorov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationParameterized and Exact Computation - 7th International Symposium, IPEC 2012, Proceedings
Pages245-253
Number of pages9
DOIs
StatePublished - 2013
Event7th International Symposium on Parameterized and Exact Computation, IPEC 2012 - Ljubljana, Slovenia
Duration: 12 Sep 201314 Sep 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7735 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Symposium on Parameterized and Exact Computation, IPEC 2012
Country/TerritorySlovenia
CityLjubljana
Period12/09/1314/09/13

Keywords

  • Automatic summarization
  • HITS algorithm
  • conceptual graphs
  • graph-based ranking algorithms

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