Abstract
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-gram corpus. First, adjectives are fed as input into the proposed system. Then, antonym pairs are extracted from the 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.
| Original language | English |
|---|---|
| Pages (from-to) | 919-927 |
| Number of pages | 9 |
| Journal | Soft Computing |
| Volume | 19 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2015 |
Fingerprint
Keywords
- Association word
- N-gram
- Oxymoron
- Sensibility
- Sentence generation
ASJC Scopus subject areas
- Software
- Geometry and Topology
- Theoretical Computer Science
Cite this
Oxymoron generation using an association word corpus and a large-scale N-gram corpus. / Yamane, Hiroaki; Hagiwara, Masafumi.
In: Soft Computing, Vol. 19, No. 4, 2015, p. 919-927.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Oxymoron generation using an association word corpus and a large-scale N-gram corpus
AU - Yamane, Hiroaki
AU - Hagiwara, Masafumi
PY - 2015
Y1 - 2015
N2 - 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-gram corpus. First, adjectives are fed as input into the proposed system. Then, antonym pairs are extracted from the 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.
AB - 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-gram corpus. First, adjectives are fed as input into the proposed system. Then, antonym pairs are extracted from the 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.
KW - Association word
KW - N-gram
KW - Oxymoron
KW - Sensibility
KW - Sentence generation
UR - http://www.scopus.com/inward/record.url?scp=84924957532&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84924957532&partnerID=8YFLogxK
U2 - 10.1007/s00500-014-1430-6
DO - 10.1007/s00500-014-1430-6
M3 - Article
AN - SCOPUS:84924957532
VL - 19
SP - 919
EP - 927
JO - Soft Computing
JF - Soft Computing
SN - 1432-7643
IS - 4
ER -