Text Representation by a Computational Model of Reading

  • J. Ignacio Serrano
  • M. Dolores del Castillo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4232)


Traditional document indexing methods, although useful, do not take into account some important aspects of language, such as syntax and semantics. Unlikely, semantic hyperspaces are mathematical and statistical-based techniques that do it. However, although they are an improvement on traditional methods, the output representation is still vector like. This paper proposes a computational model of text reading, called Cognitive Reading Indexing (CRIM), inspired by some aspects of human reading cognition, such as sequential perception, temporality, memory, forgetting and inferences. The model produces not vectors but nets of activated concepts. This paper is focused on indexing or representing documents that way so that they can be labeled or retrieved, presenting promising results. The system was applied to model human subjects as well, and some interesting results were obtained.


Latent Semantic Analysis Average Similarity Activation Spreading Text Reading Text Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • J. Ignacio Serrano
    • 1
  • M. Dolores del Castillo
    • 1
  1. 1.Instituto de Automática IndustrialSpanish Council for Scientific ResearchArganda del Rey. MadridSpain

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