2016 IEEE Symposium Series on Computational Intelligence (SSCI) 2016
DOI: 10.1109/ssci.2016.7850030
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Quality estimation for Japanese Haiku poems using Neural Network

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Cited by 4 publications
(2 citation statements)
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“…The amount of equivalent research devoted to the study of haiku or related Japanese forms is less, perhaps reflecting its lower degree of popularity in the classical and contemporary poetry scene. Kikuchi et al (2016) used a machine learning approach to estimate the artistic quality of Japanese haikus. Their model is based on word- and sound-based vectors.…”
Section: What Is Haiku?mentioning
confidence: 99%
“…The amount of equivalent research devoted to the study of haiku or related Japanese forms is less, perhaps reflecting its lower degree of popularity in the classical and contemporary poetry scene. Kikuchi et al (2016) used a machine learning approach to estimate the artistic quality of Japanese haikus. Their model is based on word- and sound-based vectors.…”
Section: What Is Haiku?mentioning
confidence: 99%
“…Haiku je uslijed svoje formalne preciznosti i pravilnosti -silabički stih od 17 slogova (5-7-5) s usječnicom i dobnicom -posljednjih godina relativno često korišten u različitim varijantama brojčanog čitanja u Japanu i izvan njega, pogotovo u slučajevima "sučitanja" s računalom u kojima ljudi samo pomažu pripremiti tekstove i parametre analize, a računalni modeli poput neuronskih mreža analiziraju, pa i estetski procjenjuju tekstove (usp. Kikuchi et al 2016). Metoda analize u ovome radu polazi od čestoće ključnih riječi -dobnica i onih koje su s njima povezane -ali interpretacija tih podataka i pjesama u kojima se nalaze ostaje isključivo u domeni autora rada.…”
Section: Brojčano čItanjeunclassified