2009 | OriginalPaper | Chapter
Revisiting N-Gram Based Models for Retrieval in Degraded Large Collections
Authors : Javier Parapar, Ana Freire, Álvaro Barreiro
Published in: Advances in Information Retrieval
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.