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Data Visualization for Kansei Analysis
http://hdl.handle.net/2237/20694
5e9325a3-f50f-4749-b40a-53b81d2d0aba
名前 / ファイル | ライセンス | アクション | |
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2014-11-05 | |||||
タイトル | ||||||
タイトル | Data Visualization for Kansei Analysis | |||||
言語 | en | |||||
著者 |
Furuhashi, Takeshi
× Furuhashi, Takeshi |
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抄録 | ||||||
内容記述 | Kansei data are multi-dimensional data. It is difficult for an analyzer to interpret data whose dimensionality is higher than three because his/her vision is used only to one -- three dimensions. Visualization by reducing the dimensionality of Kansei data to less than or equal to three dimensions could help the analyzer to understand the data. For an effective visualization, definition of distances between data is important. For the definition, axes that form a space of Kansei data should be determined first. The choice could be questions or objects. A questionnaire uses several objects and many questions. Respondents are asked to answer each question one by one by marking on a rating scale. Questions are usually used as axes for multivariate analysis. Objects are another choice for the axes. By changing our viewpoint from different axes, new relationships between questions/objects could be found. | |||||
内容記述タイプ | Abstract | |||||
内容記述 | ||||||
内容記述 | SCIS & ISIS 2010, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. December 8-12, 2010, Okayama Convention Center, Okayama, Japan | |||||
内容記述タイプ | Other | |||||
出版者 | ||||||
出版者 | 日本知能情報ファジィ学会 | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_5794 | |||||
タイプ | conference paper | |||||
書誌情報 |
SCIS & ISIS 巻 2010, p. 3-3, 発行日 2010 |
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著者版フラグ | ||||||
値 | publisher | |||||
URI | ||||||
識別子 | http://dx.doi.org/10.14864/softscis.2010.0.3.0 | |||||
識別子タイプ | DOI | |||||
URI | ||||||
識別子 | http://hdl.handle.net/2237/20694 | |||||
識別子タイプ | HDL |