From Puppy to Maturity: Experiences in Developing Terrier

By Craig Macdonald, Richard McCreadie, Rodrygo L. T. Santos, Iadh Ounis. 2012

148 citations recorded by the source corpus.

Subfields: Information Retrieval & Search

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Citations in the corpus

Pretrained Transformers for Text Ranking: BERT and Beyond (2020, background): “ions. An incomplete list, past and present, includes (in an arbitrary order) Lemur/Indri [Metzler and Croft, 2004, Metzler et al., 2004], Galago [Cartright et al., 2012], Terrier [Ounis et al., 2006, Macdonald et al., 2012], ATIRE [Trotman et al., 2012], Ivory [Lin et al., 2009], JASS [Lin and Trotm”
Anserini (2018, background): “An incomplete list includes Lemur/Indri [38, 39], Galago [15], Terrier [35, 42], ATIRE [51], Ivory [30], JASS [31], MG4J [12], [60, 61].”
Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations (2021, background): “Today, there is a vibrant ecosystem of search engines built by academic research groups such as Terrier [21] and PISA [24], common infrastructure such as ir_datasets [20], and neural ranking libraries as Capreolus [40, 41], OpenNIR [19], and OpenMatch [36].”
From MAXSCORE to Block-Max Wand: The Story of How Lucene Significantly Improved Query Evaluation Performance (2020, background): “The tradition continues to this day, with Lemur/Indri [12, 13] and Terrier [8, 14] being the most successful examples of open-source academic search engines, still popular with many researchers today.”
The Lucene for Information Access and Retrieval Research (LIARR) Workshop at SIGIR 2017 (2017, methodology): “An incomplete list includes SMART [18], Lemur/Indri [15, 16], Galago [8], Terrier [14, 17], ATIRE [20], Ivory [12], JASS [13], MG4J [6], Wumpus [21], and Zeair [25].”
Lucene4IR (2017, result): “He contrasts these products with some of the existing toolkits in IR [2, 7, 10, 14], and remarks on the latter, that “no one in industry has ever heard of them!”.”
Supporting Interoperability Between Open-Source Search Engines with the Common Index File Format (2020, background): “• Terrier [9] is an IR toolkit, first released in 2004.”
An Exploration of Approaches to Integrating Neural Reranking Models in Multi-Stage Ranking Architectures (2017, background): “To address this challenge, many academic research groups have built and shared open-source search engines with the broader community—prominent examples include Lemur/Indri [9, 10] and Terrier [7, 13].”
BERT-QE: Contextualized Query Expansion for Document Re-ranking (2020, methodology): “DPH+KL ranks the documents with DPH after expanding the original queries with Rocchio’s query expansion using Kullback-Leibler divergence (Amati, 2003; Rocchio, 1971), as implemented in the Terrier toolkit (Macdonald et al., 2012).”
NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval (2018, methodology): “platform’s (Macdonald et al., 2012) implementation of these ranking models:”
Capreolus: A Toolkit for End-to-End Neural Ad Hoc Retrieval (2020, background): “In this context, information retrieval researchers have a long history of developing shared, open-source IR toolkits, such as Indri [14], Terrier [10], and Anserini [17].”
A Summary of the COLIEE 2019 Competition (2019, methodology): “– EVORA (three runs) [20] uses Terrier IR platform with diﬀerent scoring function with two query sets (original and keyword selection) and two article database (original articles and keyword selected articles).”