Abstract
Constrained cluster analysis is a semi-supervised approach of clustering where some additional information about the clusters is incorporated as constraints. For example, sometimes, we need to consider the constraint of homogeneity among all obtained clusters. This paper presents an algorithm for constrained cluster analysis with homogeneity of clusters and shows a practical application of the algorithm in formulating survey blocks in official statistics such as the Economic Census, which reveals the effectiveness of the algorithm. In this application, travel distance is utilized considering the property of homogeneity of this clustering.
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References
Lu, Z., Leen, T.K.: Pairwise Constraints as Priors in Probabilistic Clustering. In: Constrained Clustering: Advances in Algorithms, Theory, and Applications. Chapman & Hall/CRC Data Mining and Knowledge Discovery Series. CRC Press, Taylor and Francis Group, Boca Raton (2009)
Demiriz, A., Bennett, K.P., Bradley, P.S.: Using Assignment Constraints to Avoid Empty Clusters in k-Means Clustering. In: Constrained Clustering: Advances in Algorithms, Theory, and Applications. Chapman & Hall/CRC Data Mining and Knowledge Discovery Series. CRC Press, Taylor and Francis Group, Boca Raton (2009)
Bradley, P.S., Bennett, K.P., Demiriz, A.: Constrained k-Means Clustering. Tech. rep., MSR-TR-2000-65, Microsoft Research (2000)
Malinen, M.I., Fränti, P.: Balanced K-Means for Clustering. In: Fränti, P., Brown, G., Loog, M., Escolano F., Pelillo, M. (eds.) Structural, Syntactic, and Statistical Pattern Recognition. S + SSPR 2014. Lecture Notes in Computer Science, vol. 8621. Springer, Berlin, Heidelberg (2014)
Lefkovitch, L.P.: Conditional Clustering. Biometrics 36, 43–58 (1980)
Takahashi, M., Asakawa, T., Sato-Ilic, M.: A Proposal for a Method of Forming Survey Blocks in the Economic Census for Business Frame: Development of a New Algorithm of Constrained Cluster Analysis Using the Information of Spatial Representative (in Japanese). GIS Association of Japan, D72 (2018)
Miura, H.: Three Ways to Calculate Distances Using Latitude and Longitude (in Japanese). Operations Research, vol. 60, pp. 701–705. The Operations Research Society of Japan, Tokyo (2015)
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Takahashi, M., Asakawa, T., Sato-Ilic, M. (2020). A Constrained Cluster Analysis with Homogeneity of External Criterion. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies. IDT 2020. Smart Innovation, Systems and Technologies, vol 193. Springer, Singapore. https://doi.org/10.1007/978-981-15-5925-9_26
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DOI: https://doi.org/10.1007/978-981-15-5925-9_26
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