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《Computer Applications and Software》 2014-06
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Chi Yun;Liaoning Vocational College of Business;  
Heterogeneous information networks exist everywhere in real life,and gradually play very important roles.How to classify these nodes in information networks and to rank them has become a research focus.By combining ranking and classification methods together,in this paper we present a new ranking-based iterative classification framework,build a graph-based ranking model,and make the calculated ranks distribute in every type of object.In every iteration,according to current ranking results,in ranking algorithm the graph structure adjustment is used,this makes the subnets corresponding to a specific class are emphasised,and the rest of the network is weakened.Experiment proves that the integrated classification ranking not only results in more accurate data classification method,furthermore,in each category it can provide meaningful object ranking as well,which is more effective than traditional classifications.
【CateGory Index】: TP393.02
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