A Study of Application Cosine Similarity and HOSVD for Questionnaire Data

YosukeWatanabe; Tomohiro Yoshikawa; Takeshi Furuhashi

doi:10.20965/jaciii.2015.p0100

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JACIII Vol.19 No.1 pp. 100-108

doi: 10.20965/jaciii.2015.p0100

(2015)

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A Study of Application Cosine Similarity and HOSVD for Questionnaire Data

YosukeWatanabe, Tomohiro Yoshikawa, and Takeshi Furuhashi

Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan

Received:

April 30, 2014

Accepted:

September 24, 2014

Published:

January 20, 2015

Keywords:

cosine similarity, HOSVD, questionnaire analysis, rating scale method, visualization

Abstract

Companies often carry out questionnaires, in order to gain a better grasp of consumer trends for the design of marketing strategies. The proper definition of a set of questions presents some difficulties. For example, if respondents take the meaning of two or more questions in one questionnaire to have the same/similar meanings, these questions could be rendered redundant. However, it is difficult to know beforehand how a respondent will interpret the meaning of a question. On the other hand, it is possible to assess the meaning that respondents assumed for questions, and how appropriate the set of questions is, in retrospect. In this paper, we propose a method for visualizing groups of respondents who assumed distinct meanings for questions, by applying Higher Order Singular Value Decomposition (HOSVD) to a tensor consisting of cosine similarity matrices. The proposed method is applied to a Web questionnaire dataset, and it is shown that the new method can identify the respondents’ unique understanding of the meanings of questions, which are not found using the conventional method. We also show that the proposedmethod is the most effective for the visualization of relationships between questions, among the possible ways of applying HOSVD to cosine similarity matrices.

Cite this article as:

YosukeWatanabe, T. Yoshikawa, and T. Furuhashi, “A Study of Application Cosine Similarity and HOSVD for Questionnaire Data,” J. Adv. Comput. Intell. Intell. Inform., Vol.19 No.1, pp. 100-108, 2015.

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References

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[4] C. E. Osgood, G. J. Suck, and P. H. Tannenbaum, “The Measurement of Meaning,” University of Illinois Press, 1957.
[5] T. Fukami, Y. Watanabe, T. Yoshikawa, T. Furuhashi, I. Hara, and H. Yoneda, “Discovering Minority Groups by Interactive Clustering in visible Space,” Proc. of Int. Conf. on Kansei Engineering and Emotion Research 2009 (KEER2009), Vol.3F, No.3, 2009.
[6] R. Nakasaki, H. Hasegawa, and M. Kasuga, “Evaluation of airconditioning sounds in a vehicle to determine thermal feelings using psychoacoustic parameters,” Acoustical Science and Technology, Vol.34, No.3, pp. 159-165, 2013.
[7] Y. Watanabe, T. Yoshikawa, and T. Furuhashi, “Study on Quantification of Respondent’s Conflict and Interest and Analysis Method of Questionnaire Data,” J. of Japan Society of Kansei Engineering, Vol.9, No.2, pp. 129-136, 2010.
[8] Y.Watanabe, T. Yoshikawa, and T. Furuhashi, “A Study on Comprehension of Relationship between Questions Based on Distance between Questions and Calculation of Conflict of Evaluation Value,” J. of Japan Society of Kansei Engineering, Vol.10, No.2, pp. 213-219, 2011.
[9] H.Masai, T. Yoshikawa, and T. Furuhashi, “A Visualization Method of Third-Order Tensor for Knowledge Extraction from Questionnaire Data,” Proc. of IFSA World Congress, pp. 962-967, 2013.
[10] M. A. O. Vasilescu and D. Terzopoulos, “Multilinear Analysis of Image Ensembles: TensorFaces,” Proc. ECCV-02, Copenhagen, Denmark, pp. 447-460, 2002.
[11] D. Saito, K. Yamamoto, N. Minematsu, and K. Hirose, “Voice conversion from/to arbitrary speakers based on tensor representation of speaker space,” The Institute of Electronics, Information, and Communication Engineers (IEICE), Vol.111, No.322, pp. 7-12, 2011.
[12] M. A. O. Vasilescu and D. Terzopoulos, “Multilinear Analysis of Image Ensembles: TensorFaces,” Proc. ECCV-02, Copenhagen, Denmark, pp. 447-460, 2002.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] Z. Wang, J. Li, S. Zheng, M. Moritaka, and S. Fukuda, “Factors Affecting Chinese Consumer Awareness and Acceptance of Japanese Rice,” J. of the Faculty of Agriculture, Vol.58, No.2, pp. 459-465, 2013.

[2] [2] S. Maeda, M. Futatsuka, J. Yonesaki, and M. Ikeda, “Relationship between questionnaire survey results of vibration complaints of wheelchair users and vibration transmissibility of manual wheelchair,” Environmental Health and Preventive Medicine, Vol.8, No.3, pp. 82-89, 2003.

[3] [3] J. Watada, L. Yu, M. Shibata, and M. Khalid, “An Affective Approach to Developing Marketing Strategies of Mineral Water,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.16, No.4, pp. 514-520, 2012.

[4] [4] C. E. Osgood, G. J. Suck, and P. H. Tannenbaum, “The Measurement of Meaning,” University of Illinois Press, 1957.

[5] [5] T. Fukami, Y. Watanabe, T. Yoshikawa, T. Furuhashi, I. Hara, and H. Yoneda, “Discovering Minority Groups by Interactive Clustering in visible Space,” Proc. of Int. Conf. on Kansei Engineering and Emotion Research 2009 (KEER2009), Vol.3F, No.3, 2009.

[6] [6] R. Nakasaki, H. Hasegawa, and M. Kasuga, “Evaluation of airconditioning sounds in a vehicle to determine thermal feelings using psychoacoustic parameters,” Acoustical Science and Technology, Vol.34, No.3, pp. 159-165, 2013.

[7] [7] Y. Watanabe, T. Yoshikawa, and T. Furuhashi, “Study on Quantification of Respondent’s Conflict and Interest and Analysis Method of Questionnaire Data,” J. of Japan Society of Kansei Engineering, Vol.9, No.2, pp. 129-136, 2010.

[8] [8] Y.Watanabe, T. Yoshikawa, and T. Furuhashi, “A Study on Comprehension of Relationship between Questions Based on Distance between Questions and Calculation of Conflict of Evaluation Value,” J. of Japan Society of Kansei Engineering, Vol.10, No.2, pp. 213-219, 2011.

[9] [9] H.Masai, T. Yoshikawa, and T. Furuhashi, “A Visualization Method of Third-Order Tensor for Knowledge Extraction from Questionnaire Data,” Proc. of IFSA World Congress, pp. 962-967, 2013.

[10] [10] M. A. O. Vasilescu and D. Terzopoulos, “Multilinear Analysis of Image Ensembles: TensorFaces,” Proc. ECCV-02, Copenhagen, Denmark, pp. 447-460, 2002.

[11] [11] D. Saito, K. Yamamoto, N. Minematsu, and K. Hirose, “Voice conversion from/to arbitrary speakers based on tensor representation of speaker space,” The Institute of Electronics, Information, and Communication Engineers (IEICE), Vol.111, No.322, pp. 7-12, 2011.

[12] [12] M. A. O. Vasilescu and D. Terzopoulos, “Multilinear Analysis of Image Ensembles: TensorFaces,” Proc. ECCV-02, Copenhagen, Denmark, pp. 447-460, 2002.