A link prediction method based on an improved artificial immune system and a storage medium

A technology of artificial immunity and prediction method, which is applied in the field of link prediction of artificial immune system, which can solve the problems of unreasonable quantification of different link features, high complexity of multi-dimensional feature fusion, neglect of link directionality and network dynamics, etc.

Inactive Publication Date: 2019-04-16
INFORMATION SCI RES INST OF CETC
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Problems solved by technology

[0008] The purpose of the present invention is to propose a link prediction method based on an improved artificial immune system to overcome the ignorance of link directionality and network dynamics in the prior art, the unreasonable quantification of the importance of different link features, and the complexity of multi-dimensional feature fusion Excessively high defects, thereby improving the accuracy of directed link prediction in dynamic social networks

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  • A link prediction method based on an improved artificial immune system and a storage medium
  • A link prediction method based on an improved artificial immune system and a storage medium
  • A link prediction method based on an improved artificial immune system and a storage medium

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[0093] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention. In addition, it should be noted that, for the convenience of description, only some structures related to the present invention are shown in the drawings but not all structures.

[0094] The present invention is mainly aimed at social media, obtains user personal feature information, user relationship feature information over time, and user posting status information over time, extracts these three types of features, and analyzes the correlation between the above features and the link relationship between different users feature, delete redundant features, and calculate the weight of the remaining features. The link relationship of different users includes three types, that is, whether the u...

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Abstract

The invention discloses a link prediction method based on an improved artificial immune system and a storage medium. the method comprises the steps: firstly constructing user dynamic relationship characteristics and user dynamic published content characteristics based on user network structure information and a time sequence of user published content information; Performing correlation analysis onthe link features, and endowing the link features with weights according to the importance of the features to obtain a training set with the weights; And finally, constructing a link prediction modelbased on the improved artificial immune algorithm by redefining an affinity measurement standard, a diversified affinity threshold value and a standard normal distribution variation factor. The method not only can be well suitable for the diversity of link characteristics, but also can enable the system to keep higher accuracy, and achieves the prediction of the existence and directivity of the link.

Description

technical field [0001] The invention relates to the technical field of network link prediction, in particular to a link prediction method based on an improved artificial immune system. Background technique [0002] A social network can be viewed as a graph structure in which nodes represent individuals or other entities, and edges represent interactions or relationships between nodes. Based on this relationship structure, a large number of individuals interact around an event and influence each other. Among them, the visibility of individual published text information and the invisibility of real relationships make the use of dynamic interaction networks to predict network structures a current research hotspot. As the most basic problem in relational structure analysis, link prediction has a wide range of practical application values. It can not only analyze missing data in social networks, but also can be applied to other fields, such as molecular biology, criminal investig...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/00G06N3/00
CPCG06N3/006G06Q10/04G06Q50/01
Inventor 王萌萌张峰葛建军
Owner INFORMATION SCI RES INST OF CETC
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