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Wordhoard (o.J.)
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- Abstract
- WordHoard defines a multiword unit as a special type of collocate in which the component words comprise a meaningful phrase. For example, "Knight of the Round Table" is a meaningful multiword unit or phrase. WordHoard uses the notion of a pseudo-bigram to generalize the computation of bigram (two word) statistical measures to phrases (n-grams) longer than two words, and to allow comparisons of these measures for phrases with different word counts. WordHoard applies the localmaxs algorithm of Silva et al. to the pseudo-bigrams to identify potential compositional phrases that "stand out" in a text. WordHoard can also filter two and three word phrases using the word class filters suggested by Justeson and Katz.
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WordHoard: finding multiword units (20??)
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- Abstract
- WordHoard defines a multiword unit as a special type of collocate in which the component words comprise a meaningful phrase. For example, "Knight of the Round Table" is a meaningful multiword unit or phrase. WordHoard uses the notion of a pseudo-bigram to generalize the computation of bigram (two word) statistical measures to phrases (n-grams) longer than two words, and to allow comparisons of these measures for phrases with different word counts. WordHoard applies the localmaxs algorithm of Silva et al. to the pseudo-bigrams to identify potential compositional phrases that "stand out" in a text. WordHoard can also filter two and three word phrases using the word class filters suggested by Justeson and Katz.
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Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021)
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- Source
- Evaluating information retrieval and access tasks. Eds.: Sakai, T., Oard, D., Kando, N. [https://doi.org/10.1007/978-981-15-5554-1_12]
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Liu, P.J.; Saleh, M.; Pot, E.; Goodrich, B.; Sepassi, R.; Kaiser, L.; Shazeer, N.: Generating Wikipedia by summarizing long sequences (2018)
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Perovsek, M.; Kranjca, J.; Erjaveca, T.; Cestnika, B.; Lavraca, N.: TextFlows : a visual programming platform for text mining and natural language processing (2016)
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Brown, T.B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D.M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; Amodei, D.: Language models are few-shot learners (2020)
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