Method for matching weight iteration nodes between weighting networks
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A matching method and iterative node technology, applied in the field of data mining and complex network analysis, can solve problems such as low precision and poor matching effect, and achieve the effect of improving matching accuracy and improving matching effect
Active Publication Date: 2013-07-17
ZHEJIANG UNIV OF TECH
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[0005] In order to overcome the shortcomings of poor matching effect and low precision of the existing iterative node matching method, the present
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[0026] detailed description
[0027] The present invention will be further described below in conjunction with the drawings.
[0028] Reference Figure 1 ~ Figure 6 , A weighted iterative node matching method between weighted networks. It uses the local topology information and link weight information provided by several matched node pairs to calculate the similarity between unmatched node pairs, and considers the positive and negative correlations of the link weights between networks. The impact of similarity. Based on its iterative nature, each time only a pair of unmatched nodes with the greatest similarity is selected as a matched node pair, it will be further regarded as a pair of newly revealed matched node pairs to recalculate the remaining unmatched node pairs The degree of similarity between until some termination conditions are met.
[0029] The steps of the weighted iterative node matching algorithm between weighted networks are as follows:
[0030] Step 1: Selection of ...
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Abstract
A method for matching weight iteration nodes between weighting networks includes the steps: firstly, selecting matched node pairs; secondly, calculating similarity by respectively connecting two unmatched nodes from different networks with k matched node pairs l=1, 2, ..., recording the weight of a connecting edge between vi1 and vl1 as wl1, recording the weight of a connecting edge between vj2 and vl2 as wl2 and defining the similarity of the nodes between the weighting networks as (4); thirdly, matching the nodes by selecting a pair of unmatched nodes with the highest similarity and belonging to different networks as a current matching node pair in each turn of iteration, considering the pair of unmatched nodes as a newly revealed matched node pair, turning to the second step and recalculating the similarity according to the formula (4); and fourthly, finishing matching until all the nodes in one target network are matched. By the method, matching effect and matching precision are improved.
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technical field [0001] The invention relates to data mining and complex network analysis technology, especially a node matching method. Background technique [0002] With the development of computer science, people are more and more accustomed to using networks to describe the world, such as protein networks in organisms (see literature [1] E.Ravasz, A.L.Somera, D.A.Mongru, Z.N.Oltvai, and A.L.Barabási, Hierarchical Organization of Modularity in Metabolic Networks, Science, 297(5586): 1551-1555, 2002. Namely, Lauworth, Sommer, Mongrel, Oltevoy, Barabasi, Hierarchical Modular Organization in Metabolic Networks , "Science", 297(5586):1551-1555, 2002. Literature [2] A.L.Barabási and Z.N.Oltvai, Network Biology: Understanding the Cell's Functional Organization, Nature Reviews Genetics, 5(2):101-113, 2004 .E. Barabasi, Oltwoy, Network Biology: Understanding the Functional Organization of Cells, Reviews of Nature Genetics, 5(2):101-113, 2004. Literature [3] C.Stark, B.J.Breitkreu...
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