A network characterization algorithm stability measurement method

A measurement method and stability technology, which is applied in the field of network representation algorithm stability measurement, can solve problems such as unstable representation space, and achieve accurate evaluation results

Inactive Publication Date: 2019-05-03
XI AN JIAOTONG UNIV
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Problems solved by technology

Through experiments, we found that this instability also exists in the network representation space. Compared with the word vector, the instability of the network representation algorithm has specific influencing factors, such as the DeepWalk method (refer to the DeepWalk method: Bryan ...

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  • A network characterization algorithm stability measurement method
  • A network characterization algorithm stability measurement method
  • A network characterization algorithm stability measurement method

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Embodiment Construction

[0032] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0033] In the present invention, the stability of the representation space is measured after performing representation learning on the network.

[0034] see figure 1 and Figure 4 , the present invention comprises the following steps:

[0035] Step 1: For a network G, choose a network representation method Using network representation methods on network G Multiple times, get multiple vector space sets Ω={M 1 ,M 2 ,...,M T}; where T is the size of the vector space set Ω.

[0036] Step 2: For a node i in a vector space M, by the cosine distance Calculate the K nearest neighbor node set N closest to node i, where the value of the nearest neighbor set size K is defined as:

[0037] K=0.3×|V|

[0038] Where |V| is the number of nodes, that is, the value of K is 30% of the total number of network nodes;

[0039] Step 3: For a pair of vector spaces M s and M ...

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Abstract

The invention relates to a network characterization algorithm stability measurement method, which comprises the following steps of: utilizing a network characterization algorithm to keep the characteristic of a relation between network nodes, and judging the stability by using whether a nearest neighbor set of nodes in a characterization space is consistent or not; Mapping a network into a multi-dimensional continuous dense vector space by adopting a certain representation method, and calculating the first K nodes closest to each node as the basis of stability measurement by utilizing cosine similarity; a plurality of vector spaces are generated for multiple times by adopting the same representation method for one network, and the similarity of nearest neighbor sets in the vector spaces iscalculated for one node, including the coincidence rate of the nodes and the ranking information of the coincidence nodes. According to the method, the stability performance of different algorithms on different network sets can be effectively measured, so that the influence of any factor on the stability of network characterization and the influence magnitude can be further disclosed.

Description

technical field [0001] The invention belongs to the field of network and graph representation algorithms, and relates to a method for measuring the stability of network representation algorithms. Background technique [0002] Graph-type data structures are basic discrete representations of social, biological, and information networks, but are difficult to generalize to machine learning tasks that require continuous features. So recently researchers have proposed a series of methods for learning continuous representation of nodes (retaining relationship information between nodes). Network representations have proven to be effective in downstream tasks such as node classification and clustering, link prediction, and network alignment. However, there are also certain problems in the network representation method. The Zügner method (refer to Zügner's method: Daniel Zügner, Amir Akbarnejad, and Stephan Günnemann.2018.Adversarial attacks on neural networks for graph data.InProc.o...

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Application Information

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IPC IPC(8): G06F16/901G06Q10/06
Inventor 王晨旭饶巍郭文娜王平辉刘均
Owner XI AN JIAOTONG UNIV
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