CN109286519A - A method of most powerful TOP K node in the identification network of strategy that given a discount based on side - Google Patents

A method of most powerful TOP K node in the identification network of strategy that given a discount based on side Download PDF

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Publication number
CN109286519A
CN109286519A CN201811002436.9A CN201811002436A CN109286519A CN 109286519 A CN109286519 A CN 109286519A CN 201811002436 A CN201811002436 A CN 201811002436A CN 109286519 A CN109286519 A CN 109286519A
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China
Prior art keywords
node
network
communication process
information communication
indicate
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CN201811002436.9A
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Inventor
杨旭华
熊帅
徐新黎
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Zhejiang University of Technology ZJUT
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Zhejiang University of Technology ZJUT
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Priority to CN201811002436.9A priority Critical patent/CN109286519A/en
Publication of CN109286519A publication Critical patent/CN109286519A/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/12—Discovery or management of network topologies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/091—Measuring contribution of individual network components to actual service level

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Environmental & Geological Engineering (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

A method of most powerful TOP K node in the identification network of strategy that given a discount based on side is established network model, finds out the degree of each node in network, re-records the neighbor node of each node；Public neighbours' quantity of calculate node and all neighbor nodes, weight of each edge of calculate node in information communication process again, it is weight of the node in information communication process after summation, it is arranged from high to low, the as sequence of node influence power size in a network, wherein before K node as most powerful TOP K node.The present invention is by the effect size of each edge in calculating information communication process, and to choose K node in maximizing influence problem, this method calculation amount is smaller, and accuracy is higher.

Description

It is a kind of that most powerful TOP K node in network is identified based on side discounting strategy Method
Technical field
The present invention relates to Network Science field, particularly relate to most have an impact in a kind of identification network of strategy that gives a discount based on side The method of power TOP K node.
Background technique
With the universalness of the various social medias such as microblogging, wechat, more and more people start to carry out on these platforms The publication of information comment, is forwarded, is thumbed up, and thus forms a huge social networks.In people's daily life, no Only exist social networks, the rapid development of internet, the arrival of big data era, allow people require to contact daily it is various each The network, such as high-speed rail network, highway network, electric power networks etc. that the mass data of sample and these data are combined into.Research Structure, function and their inherent law of these networks are a current hot topics, these research product promotion, There is highly important application value in the fields such as public opinion monitoring, network safety prevention, infrastructure.
Node influence power refer to by nodal information known in network, topological structure of network etc. go assessment network in it is each The importance degree of a node in the entire network, this importance degree, be generally also described as the node in a network in Disposition.With reference to past experience, the research for assessing node influence power is mainly based upon the attribute of individual node or opening up for network Structure feature is flutterred, the index for representing node influence power is provided, this usual value is bigger, indicates that node influence power is bigger.? To after the index of influence power size, the general superiority-inferiority using balancing methods such as SIR model, SIS model, Kendall's coefficients.It is right Network small in data volume, structure is single, many algorithms be all it is feasible, performance gap is little, but often in real life, The characteristic of network be all it is diversified, data volume be also it is huge, this to assessment node influence power size algorithm it is accurate Degree, efficiency have very high requirement.Once network becomes complicated, the centrality feature of node is difficult with simple algorithmic derivation It obtains, to be difficult to do exact assessment to node influence power.Therefore, an efficient, accurate assessment node influence power size Algorithm research be very important.
Summary of the invention
Low in order to overcome the shortcomings of to assess node influence power method computation complexity height, accuracy at present, the present invention proposes A kind of accuracy is higher, time complexity it is lower it is a kind of based on side give a discount strategy identification network in most powerful TOP K The method of node.
The technical solution adopted by the present invention to solve the technical problems is:
A method of most powerful TOP K node in the identification network of strategy that given a discount based on side is included the following steps:
Step 1: building one network model G (V, E) with N number of node, V are node, and E is to connect side；
Step 2: node i is arbitrarily chosen in a network, obtains the neighborhood Γ (i) of node i, Γ (i) neighborhood is contained and saved Point i has all nodes for directly connecting side；
Step 3: weight of the company side of calculate node i and node j in information communication process:
Wherein, djIndicate the degree of node j, diIndicate that the degree of node i, the degree of a node indicate there is even side with the node Neighbor node quantity, comijIndicate that common neighbours' number of node i and node j, all nodes in traversal Γ (i) calculate All even weights of the side in information communication process of egress i；
Step 4: traversal whole network repeats step 2 to step 3, and all sides for calculating whole network are passed in information Weight during broadcasting；
Step 5: traverses network, the weight summation on the side that each node is connected, as node is in information communication process Weight, then arranged from high to low, choose K node, as the TOP K in maximizing influence problem problem before ranking Node, wherein K is positive integer, K≤N.
Technical concept of the invention are as follows: by calculating effect size of each side in information communication process, to obtain Node is diffused into the size of the influence power on periphery by different sides, has the characteristics that accuracy height and computation complexity are small.
The invention has the benefit that the common neighbours for considering two nodes at a line both ends pass information in network The influence broadcast, to choose the maximum K node of influence power, this method calculation amount is smaller, and accuracy is higher.
Detailed description of the invention
Fig. 1 is network diagram, and dot is the node in network, each node has corresponding number designation, node The wired connection between node, represents the company side between node and node, and dot and the line between them constitute a network.
Specific embodiment
The present invention will be further described with reference to the accompanying drawing.
Referring to Fig.1, a method of most powerful TOP K node in the identification network of strategy that given a discount based on side, including Following steps:
Step 1: building one network model G (V, E) with N number of node, V are node, and E is to connect side；
Step 2: node i is arbitrarily chosen in a network, obtains the neighborhood Γ (i) of node i, Γ (i) neighborhood is contained and saved Point i has all nodes for directly connecting side；
Step 3: weight of the company side of calculate node i and node j in information communication process, in Fig. 1, node 2 and section Point 4 has 2 common neighbor nodes, and the degree of node 2 is 3, and the degree of node 4 is 5, then the company side between node 2 and node 4 is being believed Cease the weight in communication process
Wherein, djIndicate the degree of node j, diIndicate that the degree of node i, the degree of a node indicate there is even side with the node Neighbor node quantity, comijIndicate that common neighbours' number of node i and node j, all nodes in traversal Γ (i) calculate All even weights of the side in information communication process of egress i；
Step 4: traversal whole network repeats step 2 to step 3, and all sides for calculating whole network are passed in information Weight during broadcasting；
Step 5: traverses network, the weight summation on the side that each node is connected, as node is in information communication process Weight, then arranged from high to low, choose K node, as the TOP K in maximizing influence problem problem before ranking Node, wherein K is positive integer, K≤N.
As described above, the specific implementation step that this patent is implemented is more clear the present invention.In spirit and power of the invention In the protection scope that benefit requires, to any modifications and changes that the present invention makes, protection scope of the present invention is both fallen within.

Claims (1)

1. a kind of method of most powerful TOP K node in identification network for the strategy that given a discount based on side, which is characterized in that described Method includes the following steps:
Step 1: building one network model G (V, E) with N number of node, V are node, and E is to connect side；
Step 2: node i is arbitrarily chosen in a network, obtains the neighborhood Γ (i) of node i, Γ (i) neighborhood contains and node i There are all nodes for directly connecting side；
Step 3: weight of the company side of calculate node i and node j in information communication process:
Wherein, djIndicate the degree of node j, diIndicate that the degree of node i, the degree of a node indicate the neighbour for having even side with the node Occupy the quantity of node, comijIndicate that common neighbours' number of node i and node j, all nodes in traversal Γ (i) calculate section All even weights of the side in information communication process of point i；
Step 4: traversal whole network repeats step 2 to step 3, and all sides for calculating whole network are propagated through in information Weight in journey；
Step 5: traverses network, the weight summation on the side that each node is connected, as power of the node in information communication process Value, then arranged from high to low, K node before ranking is chosen, the TOP K section as in maximizing influence problem problem Point, wherein K is positive integer, K≤N.
CN201811002436.9A 2018-08-30 2018-08-30 A method of most powerful TOP K node in the identification network of strategy that given a discount based on side Pending CN109286519A (en)

Priority Applications (1)

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CN201811002436.9A CN109286519A (en) 2018-08-30 2018-08-30 A method of most powerful TOP K node in the identification network of strategy that given a discount based on side

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Application Number Priority Date Filing Date Title
CN201811002436.9A CN109286519A (en) 2018-08-30 2018-08-30 A method of most powerful TOP K node in the identification network of strategy that given a discount based on side

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CN109286519A true CN109286519A (en) 2019-01-29

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210224269A1 (en) * 2020-09-28 2021-07-22 Beijing Baidu Netcom Science Technology Co., Ltd. Method and apparatus of recommending information based on fused relationship network, and device and medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20210224269A1 (en) * 2020-09-28 2021-07-22 Beijing Baidu Netcom Science Technology Co., Ltd. Method and apparatus of recommending information based on fused relationship network, and device and medium
US11514063B2 (en) * 2020-09-28 2022-11-29 Beijing Baidu Netcom Science Technology Co., Ltd. Method and apparatus of recommending information based on fused relationship network, and device and medium

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Application publication date: 20190129