{"title":"该分析方法以暗峰为重点,为空间印象评价方法","authors":"Shunsuke Akai, T. Hochin, Hiroki Nomiya","doi":"10.1109/SNPD.2014.6888721","DOIUrl":null,"url":null,"abstract":"This paper proposes an analysis method of the evaluation results obtained through the Impression Evaluation Method by Space (IEMS). The IEMS uses a plane containing impression words as the Kansei space. The impression of an object is specified by circling the areas matching the impression. The degree of matching the impression is expressed by painting color. As the impression words can be moved and/or added in the IEMS, it is difficult to analyze the evaluation results obtained from many subjects. The proposed analysis method focuses on the peaks of darkness. It is called the analysis method focusing on the peaks of darkness (abbr. AM_PD). By mapping the peaks of the darkness in each evaluation result to the same Kansei space, this method can analyze characteristic impressions. In this paper, the algorithm of extracting obvious peaks automatically is proposed toward realization of the AM_PD. The parameters of the AM_PD required to extract the obvious peaks are experimentally determined. This paper shows that the obvious peaks in the evaluation results can be extracted by using this algorithm.","PeriodicalId":272932,"journal":{"name":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The analysis method focusing on peaks of darkness for the impression evaluation method by space\",\"authors\":\"Shunsuke Akai, T. Hochin, Hiroki Nomiya\",\"doi\":\"10.1109/SNPD.2014.6888721\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an analysis method of the evaluation results obtained through the Impression Evaluation Method by Space (IEMS). The IEMS uses a plane containing impression words as the Kansei space. The impression of an object is specified by circling the areas matching the impression. The degree of matching the impression is expressed by painting color. As the impression words can be moved and/or added in the IEMS, it is difficult to analyze the evaluation results obtained from many subjects. The proposed analysis method focuses on the peaks of darkness. It is called the analysis method focusing on the peaks of darkness (abbr. AM_PD). By mapping the peaks of the darkness in each evaluation result to the same Kansei space, this method can analyze characteristic impressions. In this paper, the algorithm of extracting obvious peaks automatically is proposed toward realization of the AM_PD. The parameters of the AM_PD required to extract the obvious peaks are experimentally determined. This paper shows that the obvious peaks in the evaluation results can be extracted by using this algorithm.\",\"PeriodicalId\":272932,\"journal\":{\"name\":\"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)\",\"volume\":\"174 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SNPD.2014.6888721\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2014.6888721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The analysis method focusing on peaks of darkness for the impression evaluation method by space
This paper proposes an analysis method of the evaluation results obtained through the Impression Evaluation Method by Space (IEMS). The IEMS uses a plane containing impression words as the Kansei space. The impression of an object is specified by circling the areas matching the impression. The degree of matching the impression is expressed by painting color. As the impression words can be moved and/or added in the IEMS, it is difficult to analyze the evaluation results obtained from many subjects. The proposed analysis method focuses on the peaks of darkness. It is called the analysis method focusing on the peaks of darkness (abbr. AM_PD). By mapping the peaks of the darkness in each evaluation result to the same Kansei space, this method can analyze characteristic impressions. In this paper, the algorithm of extracting obvious peaks automatically is proposed toward realization of the AM_PD. The parameters of the AM_PD required to extract the obvious peaks are experimentally determined. This paper shows that the obvious peaks in the evaluation results can be extracted by using this algorithm.