Using harmonious houses for visual pairwise comparison of multiple criteria alternatives
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Use of interactive data visualization in multi-objective forest planning
2018, Journal of Environmental ManagementCitation Excerpt :Chernoff's faces enable the DM to process these criteria in parallel and search for “certain kinds of faces” from the data based on his/her preferences. There are a lot of other graphical objects or symbols than faces, like harmonious houses (Korhonen, 1991), metroglyphs (Anderson, 1960), stick-figures (Pickett and Grinstein, 1988) and arrows (Everitt, 1978), but the main principle is the same: their use facilitates the survey between the goal variable values and the visual features of the icons. The familiarity of used icons, like faces, makes interpretation easier (Jacob, 1978).
Data mining methods for knowledge discovery in multi-objective optimization: Part A - Survey
2017, Expert Systems with ApplicationsCitation Excerpt :Other types of glyph plots are, Andrew’s curves (Andrews, 1972), star or circle glyphs (Siegel, Farrell, Goldwyn, & Friedman, 1972) and stick figures (Grinstein, Pickett, & Williams, 1989). Harmonious houses (Korhonen, 1991) inspired by Chernoff faces have been used for MOO datasets. Mosaic and spine plots (Friendly, 2002): A typical bar plot can show different variable values for a single solution as bars placed next to each other.
Supporting the intelligent MCDA user: A case study in multi-person multi-criteria decision support
2005, European Journal of Operational ResearchEliciting and mapping qualitative preferences to numeric rankings in group decision making
1999, European Journal of Operational ResearchSupporting facilitation in group support systems: Techniques for analyzing consensus relevant data
1996, Decision Support SystemsA qualitative discriminant process for scoring and ranking in group support systems
1994, Information Processing and Management
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The author wishes to thank Mr. Pekka Peiponen for computational assistance and Prof. Jyrki Wallenius for constructive and helpful comments. The research was supported, in part, by grants from the Foundation for Economic Education, and the Foundation of the Student Union of the Helsinki School of Economics, Finland.
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Pekka J. Korhonen is Professor of Statistics at the Helsinki School of Economics, Finland. He received a B.S. and M.S. in Mathematics and Ph.D. in Applied Mathematics, all from the University of Helsinki. His research interests are multiple criteria decision making, interactive computer graphics, computational statistics, the applications of such models to management problem solving. His articles have appeared in The Journal of the Operational Research Society, Management Science, Computational Statistics & Data Analysis, Quarterly Publication of the International Research Institute of Management Sciences (MNIIPU), European Journal of Operational Research, Naval Research Logistics Quarterly, Fuzzy Sets and Systems, Interfaces, Operations Research, VNIISI Publications, Belgian Journal of Operations Research, Statistics and Computer Science, Mathematical Modelling.