Revisiting N-Gram Based Models for Retrieval in Degraded Large Collections

  • Javier Parapar
  • Ana Freire
  • Álvaro Barreiro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5478)


The traditional retrieval models based on term matching are not effective in collections of degraded documents (output of OCR or ASR systems for instance). This paper presents a n-gram based distributed model for retrieval on degraded text large collections. Evaluation was carried out with both the TREC Confusion Track and Legal Track collections showing that the presented approach outperforms in terms of effectiveness the classical term centred approach and the most of the participant systems in the TREC Confusion Track.


Automatic Speech Recognition Optical Character Recognition Query Expansion Automatic Speech Recognition System Degradation Level 
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 2009

Authors and Affiliations

  • Javier Parapar
    • 1
  • Ana Freire
    • 1
  • Álvaro Barreiro
    • 1
  1. 1.IRLab, Computer Science DepartmentUniversity of A CoruñaSpain

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