Terrier Information Retrieval Platform
نویسندگان
چکیده
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.
منابع مشابه
The University of Glasgow at CLEF 2004: French Monolingual Information Retrieval with Terrier
This paper describes our participation in the CLEF 2004 French monolingual task. We used our Terrier Information Retrieval platform and experimented with query expansion and query length normalisation.
متن کاملFrom Puppy to Maturity: Experiences in Developing Terrier
The Terrier information retrieval (IR) platform, maintained by the University of Glasgow, has been open sourced since 2004. Open source IR platforms are vital to the research community, as they provide state-of-the-art baselines and structures, thereby alleviating the need to ‘reinvent the wheel’. Moreover, the open source nature of Terrier is critical, since it enables researchers to build the...
متن کاملUniversity of Glasgow at TREC 2009: Experiments with Terrier
In TREC 2009, we extend our Voting Model for the faceted blog distillation, top stories identification, and related entity finding tasks. Moreover, we experiment with our novel xQuAD framework for search result diversification. Besides fostering our research in multiple directions, by participating in such a wide portfolio of tracks, we further develop the indexing and retrieval capabilities of...
متن کاملUniversity of Glasgow at Medical Records Track: Experiments with Terrier
In our participation in the TREC 2011 Medical Records track, we investigate (1) novel voting-based approaches for identifying relevant patient visits from an aggregate of relevant medical records, (2) the effective handling of negated language in records and queries, and (3) the adoption of medical-domain ontologies for improving the representation of queries, all within the context of our Terr...
متن کاملUniversity of Glasgow at CLEF 2013: Experiments in eHealth Task 3 with Terrier
In our participation in the CLEF 2013 eHealth task 3, we investigate (1) the effectiveness of our Divergence from Randomness (DFR) framework on retrieving medical webpages, (2) the adoption of classical pseudo-relevance feedback for improving the representation of the queries, and (3) the exploitation of a collection enrichment technique for alleviating the mismatches between the terms in docum...
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