Xu, Liqun (2000) Algorithms for random ranking generation. Other thesis, Concordia University.
Given a ranking of size n , most of the existing ranking models have relatively small numbers of parameters (around n , or less). Having a small number of parameters do help facilitate the application of a ranking model. But on the other hand, it restricts the capacity for the model to describe the innate structure of a ranking population. In this report, we suggest a random ranking generator with ( n - 1) 2 parameters. The increased number of parameters enables the generator to simulate ranking populations with greater flexibility. We also suggest the use of a n x n probability matrix (P-matrix) as a device for specifying the targeted ranking population. In the P-matrix, each cell is the probability of an item being assigned a certain rank. We provide an algorithm that estimates, from a given P-matrix, the parameters for the generator. Numerical examples show that using the P-matrix based parameter estimation algorithm, the proposed generator provides better simulation to the targeted rank data.
|Divisions:||Concordia University > Faculty of Engineering and Computer Science > Computer Science and Software Engineering|
|Item Type:||Thesis (Other)|
|Pagination:||vi, 47 leaves ; 29 cm.|
|Degree Name:||Major reports (M.Comp.Sc.)|
|Program:||Computer Science and Software Engineering|
|Thesis Supervisor(s):||Lam, Clement|
|Deposited By:||Concordia University Libraries|
|Deposited On:||27 Aug 2009 17:17|
|Last Modified:||04 Nov 2016 19:33|
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