{"title":"Comparison of multiple recommendation methods of similar onomatopoeia","authors":"Dongli Han, Ryo Fukuoka, Genki Wakabayashi, Taro Shimizu, Shinnosuke Masuda","doi":"10.1109/ICCSE.2017.8085469","DOIUrl":null,"url":null,"abstract":"Onomatopoeia is a generic name for onomatopoeia and mimetic words. Using onomatopoeia can express the behavior and state of things in more detail, widening the range of communication. However, learning onomatopoeia has been a difficult task for Japanese learners. There are several existing studies aiming at a support with onomatopoeia learning, while no platform is available to help learners find similar onomatopoeia based on different criteria. In this paper, we have developed a system that proposes similar onomatopoeia for an input in three manners: one with a dictionary, and two based on statistics. A comparison with an existing system shows the effectiveness of our approach and exposes some future issues.","PeriodicalId":256055,"journal":{"name":"2017 12th International Conference on Computer Science and Education (ICCSE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th International Conference on Computer Science and Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2017.8085469","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Onomatopoeia is a generic name for onomatopoeia and mimetic words. Using onomatopoeia can express the behavior and state of things in more detail, widening the range of communication. However, learning onomatopoeia has been a difficult task for Japanese learners. There are several existing studies aiming at a support with onomatopoeia learning, while no platform is available to help learners find similar onomatopoeia based on different criteria. In this paper, we have developed a system that proposes similar onomatopoeia for an input in three manners: one with a dictionary, and two based on statistics. A comparison with an existing system shows the effectiveness of our approach and exposes some future issues.
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