caa a22 4500 605469962 CHVBK 20210128100325.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00500-014-1430-6 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1430-6 Oxymoron generation using an association word corpus and a large-scale N -gram corpus [Elektronische Daten] [Hiroaki Yamane, Masafumi Hagiwara] Oxymorons are combinations of contradictory or incongruous words and are typically used to draw readers' attention to a text. This paper proposes a method to generate oxymorons using an association word corpus and a large-scale $$N$$ N -gram corpus. First, adjectives are fed as input into the proposed system. Then, antonym pairs are extracted from the $$N$$ N -gram corpus. Using the antonym pairs and the association word corpus, candidates are generated. Candidates are finalized or eliminated according to their suitability and attractiveness. To determine suitability, pointwise mutual information (PMI) is employed to exclude grammatically unnatural expressions. To determine attractiveness, PMI, gap of frequency of the oxymoron candidates, and WordNet are used. The generated combinations of oxymorons indicate the potential effectiveness of the proposed method. Springer-Verlag Berlin Heidelberg, 2014 Oxymoron nationallicence Association word nationallicence $$N$$ N -gram nationallicence Sentence generation nationallicence Sensibility nationallicence Yamane Hiroaki Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, 223-8522, Kohoku, Yokohama, Japan aut Hagiwara Masafumi Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, 223-8522, Kohoku, Yokohama, Japan aut Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 919-927 1432-7643 19:4<919 2015 19 500 https://doi.org/10.1007/s00500-014-1430-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1430-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yamane Hiroaki Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, 223-8522, Kohoku, Yokohama, Japan aut NATIONALLICENCE 700 1- Hagiwara Masafumi Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, 223-8522, Kohoku, Yokohama, Japan aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 919-927 1432-7643 19:4<919 2015 19 500