Most cited
This page lists all time most cited articles for this title. Please use the publication date filters on the left if you would like to restrict this list to recently published content, for example to articles published in the last three years. The number of times each article was cited is displayed to the right of its title and can be clicked to access a list of all titles this article has been cited by.
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A cross-corpus study of subjectivity identification using unsupervised learning†
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- Published online by Cambridge University Press:
- 16 August 2011, pp. 375-397
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Learning keyphrases from corpora and knowledge models
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- Published online by Cambridge University Press:
- 10 September 2019, pp. 293-318
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Paraphrasing spoken Chinese using a paraphrase corpus
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- Published online by Cambridge University Press:
- 10 November 2005, pp. 417-434
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Efficient dictionary-based text rewriting using subsequential transducers†
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- Published online by Cambridge University Press:
- 01 December 2007, pp. 353-381
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Editorial note
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- Published online by Cambridge University Press:
- 19 December 2018, pp. 1-4
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Text Mining with R: A Tidy Approach, by Julia Silge and David Robinson. Sebastopol, CA: O’Reilly Media, 2017. ISBN 978-1-491-98165-8. XI + 184 pages.
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- Published online by Cambridge University Press:
- 12 January 2021, pp. 137-139
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Cluster-based ensemble learning model for improving sentiment classification of Arabic documents
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- Published online by Cambridge University Press:
- 01 June 2023, pp. 1-39
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Reducing repetition in convolutional abstractive summarization
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- 24 November 2021, pp. 81-109
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Best parse parsing with Earley's and Inside algorithms on probabilistic RTN
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- 12 September 2008, pp. 147-161
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Machine Learning for Text, by Charu C. Aggarwal, New York, Springer, 2018. ISBN 9783319735306. XXIII + 493 pages.
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- Published online by Cambridge University Press:
- 12 January 2021, pp. 541-543
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Improving semantic coverage of data-to-text generation model using dynamic memory networks
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- 31 May 2023, pp. 1-26
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A transformer-based multi-task framework for joint detection of aggression and hate on social media data
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- 11 April 2023, pp. 1495-1515
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