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The detection of allusive text reuse is particularly challenging due to the sparse evidence on which allusive references rely---commonly based on none or very few shared words.
Indexing by latent semantic analysis
Scott Deerwester, Susan T. Dumais, George W. Furnas, Thomas K. Landauer, and Richard Harshman. 1990 · 1990
Earlier work this paper cites.
The TREC-8 Question Answering Track Report
Ellen M Voorhees. 1999 · 1999
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Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures
Alexander Budanitsky and Graeme Hirst. 2001 · 2001
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Intertextuality: Debates and Contexts
Mary Orr. 2003 · 2003
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A Computational Model of Text Reuse in Ancient Literary Texts
John Lee. 2007 · 2007
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Inter-Coder Agreement for Computational Linguistics
Ron Artstein and Massimo Poesio. 2008 · 2008
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The logic and discovery of textual allusion
David Bamman and Gregory Crane. 2008 · 2008
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Introduction to information retrieval , volume 39
Hinrich Schütze, Christopher D Manning, and Prabhakar Raghavan. 2008 · 2008
Earlier work this paper cites.
Discovering Multilingual Text Reuse in Literary Texts
David Bamman and Gregory Crane. 2009 · 2009
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A ‘key to all quotations’? A corpus-based parameter model of intertextuality
Regula Hohl Trillini and Sixta Quassdorf. 2010 · 2010
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The Latin WordNet project
Stefano Minozzi. 2010 · 2010
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Neil Coffee, Jean-Pierre Koenig, Shakthi Poornima, Christopher W Forstall, Roelant Ossewaarde, and Sarah L Jacobson. 2012 · 2012
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Informationstechnische Aspekte des Historical Text Re-use
Marco Büchler. 2013 · 2013
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
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New Ways of Searching with Biblindex, the online Index of Biblical Quotations in Early Christian Literature
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Waleed Ammar, George Mulcaire, Yulia Tsvetkov, Guillaume Lample, Chris Dyer, and Noah A Smith. 2016 · 2016
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Non-literal text reuse in historical texts: An approach to identify reuse transformations and its application to bible reuse
Maria Moritz, Andreas Wiederhold, Barbara Pavlek, Yuri Bizzoni, and Marco Büchler. 2016 · 2016
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The sense of a connection: Automatic tracing of intertextuality by meaning
Walter Scheirer, Christopher Forstall, and Neil Coffee. 2016 · 2016
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Ron Artstein. 2017 · 2017
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Laurence Mellerin. 2014 · 2014
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Grigori Sidorov, Alexander Gelbukh, Helena Gómez-Adorno, and David Pinto. 2014 · 2014
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David A. Smith, Ryan Cordel, Elizabeth Maddock Dillon, Nick Stramp, and John Wilkerson. 2014 · 2014
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Modeling the scholars: Detecting intertextuality through enhanced word-level n-gram matching
Christopher Forstall, Neil Coffee, Thomas Buck, Katherine Roache, and Sarah Jacobson. 2015 · 2015
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From word embeddings to document distances
Matt Kusner, Yu Sun, Nicholas Kolkin, and Kilian Weinberger. 2015 · 2015
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Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
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Simbow at semeval-2017 task 3: Soft-cosine semantic similarity between questions for community question answering
Delphine Charlet and Geraldine Damnati. 2017 · 2017
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A Method for Human-Interpretable Paraphrasticality Prediction
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Improving lemmatization of non-standard languages with joint learning
Enrique Manjavacas, Ákos Kádár, and Mike Kestemont. (in press) · 2019
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