Mining the change of consensus from group ranking decisions

Author(s):  
Li-Chen Cheng ◽  
Min-Ting Lai
Keyword(s):  
Author(s):  
Lingjun Li ◽  
Xinxin Zhao ◽  
Guoliang Xue ◽  
Gabriel Silva

Author(s):  
Junchang Li ◽  
Jiantong Zhang ◽  
Ye Ding

The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients choose the ideal M-medical APP, we proposed a novel multiple attribute group decision making algorithm based on group compromise framework, which need not determine the weight of decision-maker. The algorithm utilized an uncertain multiplicative linguistic variable to measure the individual original preference to express the real evaluation information as much as possible. The attribute weight was calculated by maximizing the differences among alternatives. It determined the individual alternatives ranking according to the net flow of each alternative. By solved the 0–1 optimal model with the objective of minimizing the differences between individual ranking, the ultimate group compromise ranking was obtained. Then we took 10 well-known M-medical APPs in Chinese as an example, we summarized service categories provided for users and constructed the assessment system consisting of 8 indexes considering the service quality users are concerned with. Finally, the effectiveness and superiority of the proposed method and the consistency of ranking results were verified, through comparing the group ranking results of 3 similar algorithms. The experiments show that group compromise ranking is sensitive to attribute weight.


2018 ◽  
Vol 17 (03) ◽  
pp. 741-761
Author(s):  
Li-Ching Ma

Group-ranking problems are widely encountered decision problems which combine personal preferences to form an integrated group priority; however, providing support to solve group-ranking problems is difficult because each person has his/her own viewpoint regarding how such decisions should be made. In addition, many researchers have shown that visual aids are useful in helping users comprehend decision backgrounds. Therefore, determining how to support the group-ranking process and providing visual aids is an important issue. This study proposes a novel graphical approach to discover group consensus sequences. First, a counting-based data mining approach is constructed to discover a consensus preference matrix. Second, an ordinal Gower plot can be drawn whereby group consensus sequences can be directly observed. Unlike previous methods, the proposed approach can discover group consensus sequences without involving tedious candidate generation and exhaustive search processes, derive a total ranking list, as well as provide visual aids to users.


1989 ◽  
Vol 69 (3) ◽  
pp. 619-626 ◽  
Author(s):  
M. H. FAHMY ◽  
P. M. FLIPOT ◽  
M. S. WOLYNETZ ◽  
J. E. COMEAU

Sets of twin lambs from both sexes representing 11 genetic groups were fed either concentrate (HE) or roughage (LE) diets from weaning to 32 kg liveweight. One lamb from each set received the HE diet while the other received the LE diet. Data on average daily gain (ADG), relative ADG (RADG) and feed conversion ratio (FCR) were analyzed to test for the presence of a genotype × diet interaction; this effect was significant for RADG. Although the ranking of the genetic groups with respect to RADG depended upon diet, the group ranking highest on HE was also the highest on LE. The set of twins × diet interaction was not significant for ADG or RADG. The results support the present practice in test stations of feeding lambs concentrate rations to identify their potential for growth and basing growth comparisons on a within genetic group basis. Key words: Genotype × diet interaction, growth rate, feed conversion ratio


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