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ValueCharts: analyzing linear models expressing preferences and evaluations
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Proceedings of the working conference on Advanced visual interfaces table of contents
Gallipoli, Italy
SESSION: Improving visualization table of contents
Pages: 150 - 157  
Year of Publication: 2004
ISBN:1-58113-867-9
Authors
Giuseppe Carenini  University of British Columbia, Vancouver, B.C., Canada
John Loyd  University of British Columbia, Vancouver, B.C., Canada
Sponsors
: Regione Puglia
: Provincia di Lecce
: Comune di Corigliano d'Otranto
: Camera di Commercio di Brindisi
: Monte dei Paschi di Siena
: Università degli Studi di Bari
: Università degli Studi di Lecce
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
: Università degli Studi dell'Aquila
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper we propose ValueCharts, a set of visualizations and interactive techniques intended to support decision-makers in inspecting linear models of preferences and evaluation. Linear models are popular decision-making tools for individuals, groups and organizations. In Decision Analysis, they help the decision-maker analyze preferential choices under conflicting objectives. In Economics and the Social Sciences, similar models are devised to rank entities according to an evaluative index of interest. The fundamental goal of building models expressing preferences and evaluations is to help the decision-maker organize all the information relevant to a decision into a structure that can be effectively analyzed. However, as models and their domain of application grow in complexity, model analysis can become a very challenging task. We claim that ValueCharts will make the inspection and application of these models more natural and effective. We support our claim by showing how ValueCharts effectively enable a set of basic tasks that we argue are at the core of analyzing and understanding linear models of preferences and evaluation.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Giuseppe Carenini: colleagues
John Loyd: colleagues