Credibility-based Algorithm for Merging Vote Lists
Author(s): YANG Hong-guo, SHEN De-rong, KOU Yue, YU Ge, School of Computer Science & Engineering, Northeastern University
Pages: 165-168+173
Year: 2016 Issue: 2
Journal: Journal of Northeastern University(Natural Science)
Keyword: list; voting system; lists merging; credibility; comprehensive ranking;
Abstract: In a voting system,each voter makes a preferential list about candidates,thus a large amount of ordered lists are obtained. To get a comprehensive voting result from these lists,an effective lists merging algorithm is required,which can analyze these lists data and output a comprehensive list. A merging algorithm based on credibility is proposed. Through analyzing the data of lists,numerous ranking messages are extracted,then the credibility of them is formulated and measured,with which the final comprehensive list is computed such that those ranking messages with high credibility could play a more influential role in the final ranking result.Experimental results fully indicate that the algorithm proposed can dig out the credibility about ranking information more effectively,thus attaining the merging results more accurately.
Pages: 165-168+173
Year: 2016 Issue: 2
Journal: Journal of Northeastern University(Natural Science)
Keyword: list; voting system; lists merging; credibility; comprehensive ranking;
Abstract: In a voting system,each voter makes a preferential list about candidates,thus a large amount of ordered lists are obtained. To get a comprehensive voting result from these lists,an effective lists merging algorithm is required,which can analyze these lists data and output a comprehensive list. A merging algorithm based on credibility is proposed. Through analyzing the data of lists,numerous ranking messages are extracted,then the credibility of them is formulated and measured,with which the final comprehensive list is computed such that those ranking messages with high credibility could play a more influential role in the final ranking result.Experimental results fully indicate that the algorithm proposed can dig out the credibility about ranking information more effectively,thus attaining the merging results more accurately.
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