Ranking list aggregation method with local information
A technology of local information and aggregation methods, applied in the direction of instruments, data processing applications, resources, etc., can solve the problems of slow aggregation speed and insufficient accuracy of aggregation results.
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[0054] in figure 1 In, a ranking list aggregation method with partial information includes the following steps:
[0055] Step 1: Put N rankers e 1 ,...E i ,...E N For M ranked objects f 1 ,...F j ,...F M N initial ranking list R' 1 ,...R' i ,...R' N Matrix, get the ranking matrix R, R=[r ij ],1≤i≤N, 1≤j≤M; r ij Is a non-negative number, which means f j Ranker e i Given ranking list R' i Ranked r ij Position; the i-th row R(i,:) of the matrix corresponds to the ranker e i The good reviews are given first and the bad reviews are ranked second in the list R' i , R ij Corresponding ranking list In a;
[0056] As in Example 1, there are currently 8 students {e 1 ,e 2 ,e 3 ,e 4 ,e 5 ,e 6 ,e 7 ,e 8 }To 5 teachers{f 1 ,f 2 ,f 3 ,f 4 ,f 5 }The ranking list of favorable comments first and negative comments second, as shown in the following table:
[0057]
[0058] Then the specific method to obtain the ranking matrix R is:
[0059] Step 1.1: Get the set of rankers E={e 1 ,e 2 ,e 3 ,e 4 ,e...
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