Abstract
Terrier is a modular platform for the rapid development of large-scale Information Retrieval (IR) applications. It can index various document collections, including TREC and Web collections. Terrier also offers a range of document weighting and query expansion models, based on the Divergence From Randomness framework. It has been successfully used for ad-hoc retrieval, cross-language retrieval, Web IR and intranet search, in a centralised or distributed setting.
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© 2005 Springer-Verlag Berlin Heidelberg
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Ounis, I., Amati, G., Plachouras, V., He, B., Macdonald, C., Johnson, D. (2005). Terrier Information Retrieval Platform. In: Losada, D.E., Fernández-Luna, J.M. (eds) Advances in Information Retrieval. ECIR 2005. Lecture Notes in Computer Science, vol 3408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31865-1_37
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DOI: https://doi.org/10.1007/978-3-540-31865-1_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25295-5
Online ISBN: 978-3-540-31865-1
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