CN102611588B - Method for detecting overlapped community network based on automatic phase conversion clustering - Google Patents
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Abstract
The invention provides a method for detecting an overlapped community network based on an automatic phase conversion clustering. By adopting the detecting method, the problems that the processing speed is slow, the complexity is high and the community structures and the number of communities need to be known in advance in a process of detecting overlapped communities are overcome. The method is realized by the steps of (1) generating network adjacency matrixes; (2) initializing; (3) updating node phases; (4) processing updated node phases; (5) judging if the updated node phases are stable; (6) counting the number of nodes in subintervals; and (7) outputting network community division results. According to the method, the step of updating the node phases is a discrete iteration process, the phase solving process is accelerated, the parallel processing capability is improved, the inherent frequencies and the known community structures of nodes do not need to be set in advance, the complexity of the network community detection is lowered, and the communities and the overlapped nodes in a network can be effectively detected.
Description
Technical field
The invention belongs to networking technology area, further relate to the overlapping community network detection method based on automatic phase transformation cluster in data mining technology field.By phase dispersion iteration, in the situation that not needing known community structure and community's number, can effectively detect the overlapping nodes between each community and the community of network.
Background technology
The research that Web Community is detected comes from sociological research work, be characterized in that the connection between identical community interior nodes is denser, and connection between different communities intermediate node is more sparse, community structure is one of the most general in community network and most important topological attribute, finds and discloses the community structure of network and contribute to people more effectively to analyze topology of networks, understand the hiding rule in function, the discovering network of network and predict its behavior etc.The algorithm that a lot of Web Communities are detected has been proposed at present, but most of algorithm is devoted to find independent non-overlapping community structure, and in real network, between community structure, often there is overlap problem, exist some nodes to belong to the situation of Liang Ge community, such as in community activity, a people may not only participate in football club but also participated in table tennis club, and this people is just likely in two different communities of club.
The patent " community network method for building up and device and community discovery method and device " (number of patent application 200910135387.0, publication number CN 101877711A) of Huawei Tech Co., Ltd's application.The Web Community of the method finds that device mainly comprises merging module, similarity calculation module and community discovery result community module.The method Shortcomings part is, for given network, each merge module all must Network Search in maximum corresponding two nodes of similarity, then calculate and merge the new node of module gained and the similarity of this new node adjacent node, this patent application computational process is too complicated, similarity between time computing node that need to be longer, the length that expends time in, has reduced Web Community's detection efficiency.
The people such as J.A.Almendral are being published in the overlapping community detection method that has proposed a kind of oscillator synchronization Network Based for 2010 in the article " Dynamics of overlapping structures in modular networks " on PHYSICAL REVIEW E periodical.The method is utilized Kuramoto oscillator model, each node in network is corresponding one by one with an oscillator, for given network topology structure, the in the situation that of known community structure and community's number, the natural frequency of a certain community of setting network interior nodes is W1, the natural frequency of all the other community's interior nodes is W2, utilize the changing value of Kuramoto oscillator model solution phase place, then calculate the overlapping index of each node, draw all the other intercommunal overlapping nodes of this community and network, repeat above step, draw the overlapping nodes between other communities.The method Shortcomings part is, for given network topology structure, must, in the case of the community structure of known network and community's number, can obtain the overlapping nodes between community, limited the range of application of the method; Meanwhile, the method is by separating the changing value of differential equation phase place, in the time that the nodes of network is more, solve the differential equation and will become very slow, and must set the natural frequency of node before solving the changing value of phase place, and increase the complex nature of the problem, reduce community's detection efficiency.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, propose a kind of overlapping community network detection method based on automatic phase transformation cluster, detect with the overlapping community realizing in real network.The present invention passes through constantly the more phase place of new node, and the phase place while stablizing according to each node, detects each community and the overlapping nodes of network, detects thereby effectively realized overlapping community network.
Concrete steps of the present invention are as follows:
(1) overlapping community network to be detected is generated to the adjacency matrix corresponding with this network.
(2) initialization
The random number of random generation and number of network node same number within the scope of [a, a] phase value, the initial phase using each random number as each node.
(3) new node phase place more
To under the phase place substitution before each node updates, establish an equation, obtain a new phase place after this node updates:
y＝x+C1×(M-x)+C2×(x-N)
Wherein, y is the phase place after node updates; X is the phase place before node updates; C1 is the control parameter of weighing the closing speed of controlling identical community interior nodes phase place, and C2 weighs the control parameter away from speed of controlling different communities intermediate node phase place, C1, C2 (0,1] choose in scope; The average phase of all nodes that M representative and node have a fillet before renewal; The average phase of all nodes that N representative and node do not have a fillet before renewal.
(4) process and upgrade posterior nodal point phase place
If while existing phase value to be greater than the phase place of a in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is positive phase place, be that each positive node phase place multiplies each other with compression ratio r1 respectively by phase value, making phase value is that each positive node phase place is distributed between [a, a] phase value; If while there is the phase place of be less than-a of phase value in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is negative phase place, be that each node phase place of bearing multiplies each other with compression ratio r2 respectively by phase value, making phase value is that each node phase place of bearing is distributed between [a, a] phase value.
(5) judge whether the phase place of upgrading posterior nodal point is stablized
Phase place by the phase place after each node updates and before upgrading is subtracted each other, obtain a difference, if this difference is less than 0, this difference is asked to absolute value, in the difference of all nodes, choose a wherein difference of difference maximum, if this maximum difference is less than threshold epsilon, 0 < ε < 1, think that the phase place of all nodes tends towards stability, enter next step, otherwise the phase place using the phase place after each node updates before this node upgrades, returns to step (3) next time.
(6) statistics subinterval node number
In the time of the phase stabilization of all nodes, [a, a] phase value is evenly divided into the subinterval that several length are len, the number of the phase place of adding up each subinterval interior nodes in this subinterval scope interior nodes.
(7) output network community division result
Subinterval interior nodes number is greater than between 0 adjacent subarea and is divided into one group, in all subintervals in this group, search for the maximum of subinterval node number, if this maximum is greater than threshold value T, 1≤T≤5, the community that in this group, node corresponding to all subintervals is network, otherwise, the overlapping nodes that in this group, node corresponding to all subintervals is network.
Compared with prior art there is following advantage in the present invention:
The first, due to the present invention more the phase place of new node be the process of a discrete iteration, accelerated phase solution process, improve parallel processing capability, meanwhile, do not needed to set in advance the natural frequency of each node, overcome in prior art process slower, the problem that complexity is higher.Solution node phase place change procedure of the present invention is a parallel processing process, does not need to set in advance the natural frequency of each node, can greatly reduce the complexity that Web Community is detected, and improves detection efficiency.
Second, because the present invention has introduced C1, two of C2 control parameter, C1 controls the closing speed of identical community interior nodes phase place, C2 control different communities intermediate node phase place away from speed, by phase dispersion iteration, make the phase place of identical community interior nodes more and more approaching, and the phase place of different communities intermediate node more and more away from, simultaneously the phase place of overlapping nodes is between the phase place of two different communities nodes, thereby detects the overlapping nodes between each community and the community of network.The present invention has overcome and in prior art, has carried out overlapping community while detecting, must prior known community structure and the problem of community's number.Phase place when the present invention stablizes according to each node, can detect the overlapping nodes between each community and community accurately.
Brief description of the drawings
Fig. 1 is flow chart of the present invention;
Fig. 2 is the schematic diagram of the present invention to karate club network simulation result;
Fig. 3 is the schematic diagram of the present invention to dolphin community network simulation result.
Embodiment
Below in conjunction with Fig. 1, specific embodiment of the invention step is described in further detail.
Step 1. generating network adjacency matrix
Overlapping community network to be detected is generated to the adjacency matrix corresponding with this network; From network, choose arbitrarily two nodes, if having fillet between these two nodes, in adjacency matrix, corresponding element is 1, otherwise is 0.
In the embodiment of step 1 of the present invention, overlapping community network to be detected adopts karate club network, this club is by 34 member compositions, the corresponding node of each member, certain between member is related to the fillet between corresponding node, chooses arbitrarily two nodes, if have fillet between these two nodes, in adjacency matrix, corresponding element is 1, otherwise is 0, obtains thus corresponding adjacency matrix as follows:
Step 2. initialization
The corresponding phase place of each node in network, the upper bound of phase value is a, the random number of random generation and number of network node same number within the scope of [a, a] phase value, the initial phase using each random number as each node; Wherein, the span of the upper bound a of phase value is 5≤a≤100.
In the embodiment of step 2 of the present invention, number of network node is 34, the upper bound a=50 of phase value, 34 random numbers of random generation within the scope of [50,50] phase value, the random number of generation is [34.871,-41.682, ,-33.336,9.6371], initial phase using each random number as each node, be about to-34.871 initial phases as first node, incite somebody to action-41.682 as second node initial phase, the like.
Step 3. is new node phase place more
To under the phase place substitution before each node updates, establish an equation, obtain a new phase place after this node updates:
y＝x+C1×(M-x)+C2×(x-N)
Wherein, y is the phase place after node updates; X is the phase place before node updates; C1 is the control parameter of weighing the closing speed of controlling identical community interior nodes phase place, and C2 weighs the control parameter away from speed of controlling different communities intermediate node phase place, C1, C2 (0,1] choose in scope; The average phase of all nodes that M representative and node have a fillet before renewal; The average phase of all nodes that N representative and node do not have a fillet before renewal.
In the embodiment of step 3 of the present invention, will under the phase place substitution before each node updates, establish an equation, obtain a new phase place after this node updates:
y＝x+C1×(M-x)+C2×(x-N)
Wherein, y is the phase place after node updates; X is the phase place before node updates; C1 is the control parameter of weighing the closing speed of controlling identical community interior nodes phase place, and C2 weighs the control parameter away from speed of controlling different communities intermediate node phase place, C1=0.02, C2=0.005; The average phase of all nodes that M representative and node have a fillet before renewal; The average phase of all nodes that N representative and node do not have a fillet before renewal.
Step 4. is processed the phase place of upgrading posterior nodal point
If while existing phase value to be greater than the phase place of a in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is positive phase place, be that each positive node phase place multiplies each other with compression ratio r1 respectively by phase value, making phase value is that each positive node phase place is distributed between [a, a] phase value; If while there is the phase place of be less than-a of phase value in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is negative phase place, be that each node phase place of bearing multiplies each other with compression ratio r2 respectively by phase value, making phase value is that each node phase place of bearing is distributed between [a, a] phase value; Wherein, compression ratio r1 and r2 obtain according to the following formula: compression ratio r1=a/b, and compression ratio r2=-a/c, the upper bound that a is phase value, b is the maximum phase in all node phase places after upgrading, c is the minimum phase in all node phase places after upgrading.
In the embodiment of step 4 of the present invention, if while existing phase value to be greater than 50 phase place in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is positive phase place, be that each positive node phase place multiplies each other with compression ratio r1 respectively by phase value, making phase value is that each positive node phase place is distributed between [50,50] phase value; If while existing phase value to be less than-50 phase place in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is negative phase place, be that each node phase place of bearing multiplies each other with compression ratio r2 respectively by phase value, making phase value is that each node phase place of bearing is distributed between [50,50] phase value; Wherein, compression ratio r1 and r2 obtain according to the following formula: compression ratio r1=50/b, and compression ratio r2=-50/c, b is the maximum phase in all node phase places after upgrading, c is the minimum phase in all node phase places after upgrading.
Step 5. judges whether the phase place of upgrading posterior nodal point is stablized
Phase place by the phase place after each node updates and before upgrading is subtracted each other, obtain a difference, if this difference is less than 0, this difference is asked to absolute value, in the difference of all nodes, choose a wherein difference of difference maximum, if this maximum difference is less than threshold epsilon, 0 < ε < 1, think that the phase place of all nodes tends towards stability, enter next step, otherwise the phase place using the phase place after each node updates before this node upgrades, returns to step (3) next time.
In the embodiment of step 5 of the present invention, phase place by the phase place after each node updates and before upgrading is subtracted each other, obtain a difference, if this difference is less than 0, this difference is asked to absolute value, in the difference of all nodes, choose a wherein difference of difference maximum, if this maximum difference is less than threshold value 0.001, think that the phase place of all nodes tends towards stability, enter next step, otherwise the phase place using the phase place after each node updates before this node upgrades, returns to step (3) next time.In the time upgrading 1300 times, the maximum of phase difference value is less than 0.001, and the phase place of all nodes tends towards stability.
Step 6. is added up subinterval node number
In the time of the phase stabilization of all nodes, [a, a] phase value is evenly divided into the subinterval that several length are len, the number of the phase place of adding up each subinterval interior nodes in this subinterval scope interior nodes; Wherein, the upper bound that a is phase value, the span of the length l en in each subinterval is 1≤len≤5.
In the embodiment of step 6 of the present invention, in the time of the phase stabilization of all nodes, will [50,50] phase value is evenly divided into the subinterval that 20 length are 5, and subinterval is expressed as S1:[-50, and-45], S2:[-45,-40] ..., S19:[40,45], S20:[45,50], the phase place of each subinterval interior nodes of statistics is as shown in the table in the number of this subinterval scope interior nodes:
| S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | S9 | S10 |
| 3 | 2 | 0 | 0 | 3 | 2 | 2 | 1 | 0 | 2 |
| S11 | S12 | S13 | S14 | S15 | S16 | S17 | S18 | S19 | S20 |
| 1 | 0 | 0 | 1 | 2 | 2 | 0 | 2 | 3 | 8 |
Step 7. output network community division result
Subinterval interior nodes number is greater than between 0 adjacent subarea and is divided into one group, in all subintervals in this group, search for the maximum of subinterval node number, if this maximum is greater than threshold value T, 1≤T≤5, the community that in this group, node corresponding to all subintervals is network, otherwise, the overlapping nodes that in this group, node corresponding to all subintervals is network.
In the embodiment of step 7 of the present invention, the group that subinterval interior nodes number is greater than 0 adjacent subinterval after dividing is: G1:{S1, S2}, G2:{S5, S6, S7, S8}, G3:{S10, S11}, G4:{S14, S15, S16}, G5:{S18, S19, S20}, threshold value T=2, in G1 group, the maximum of subinterval node number is 3, the node { 5 of this group correspondence, 6, 7, 11, 17} is defined as a community of network, in G2 group, the maximum of subinterval node number is 3, the node { 1 of this group correspondence, 2, 4, 8, 12, 13, 18, 22} is defined as a community of network, in G3 group, the maximum of subinterval node number is 2, the node { 3 of this group correspondence, 14, 20} is defined as the overlapping nodes of network, in G4 group, the maximum of subinterval node number is 2, the node { 9 of this group correspondence, 10, 29, 31, 32} is defined as the overlapping nodes of network, in G5 group, the maximum of subinterval node number is 8, the node { 15 of this group correspondence, 16, 19, 21, 23, 24, 25, 26, 27, 28, 30, 33, 34} is defined as a community of network, thereby realize community's detection for the treatment of Sampling network, each community and the overlapping nodes of network are detected.
Below in conjunction with accompanying drawing 2 accompanying drawings 3, simulated effect of the present invention is further described.
1. simulated conditions:
Be to use Matlab 2009a to carry out emulation in core 22.4GHZ, internal memory 2G, WINDOWS XP system at CPU.
2. emulation content:
Choose karate club network and dolphin community network as simulation object.Karate club network is made up of 34 nodes, and each node represents a clubbite, certain relation between the fillet line-up of delegates between node; Dolphin community network is made up of 62 nodes, and each node represents a dolphin, and the fillet between node represents certain social relationships between dolphin.The parameter that in emulation, two networks are used is as shown in the table:
| Network | a | C1 | C2 | ε | len | T |
| Karate club network | 50 | 0.02 | 0.005 | 0.001 | 5 | 2 |
| Dolphin community network | 50 | 0.3 | 0.022 | 0.001 | 4 | 2 |
Under above Parameter Conditions to the schematic diagram of karate club network simulation result as shown in Figure 2: in figure, oval corresponding node { 5, 6, 7, 11, 17} is a community of network, circular corresponding node { 1, 2, 4, 8, 12, 13, 18, 22} is a community of network, the node { 3 that triangle is corresponding, 14, 20, 9, 10, 29, 31, 32} is the overlapping nodes of network, the node { 15 that square is corresponding, 16, 19, 21, 23, 24, 25, 26, 27, 28, 30, 33, 34} is a community of network, overlapping nodes { 3, 14, 20, 9, 10, 29, 31, 32} has and is connected in real network and between Liang Ge community, verify validity of the present invention.
Under above Parameter Conditions to the schematic diagram of dolphin community network simulation result as shown in Figure 3: in figure, the node { community that 5,6,9,13,17,22,25,26,27,31,32,41,48,54,56,57,60} is network that square is corresponding; The circular corresponding node { community that 0,2,3,4,8,10,11,12,14,15,16,18,20,21,23,24,29,33,34,35,37,38,40,42,43,44,45,46,47,49,50,51,52,53,55,58,59,61} is network; { overlapping nodes that 1,7,19,28,30,36,39} is network, { 1,7,19,28,30,36,39} has and is connected overlapping nodes the node that triangle is corresponding in real network and between Liang Ge community, has verified validity of the present invention.
Can find out from above explanation, can detect each community and the overlapping nodes of network based on the overlapping community network detection method of automatic phase transformation cluster, realize the detection of overlapping community network.
Claims (4)
1. the overlapping community network detection method based on automatic phase transformation cluster, concrete steps are as follows:
(1) overlapping community network to be detected is generated to the adjacency matrix corresponding with this network;
(2) initialization
The random number of random generation and number of network node same number within the scope of [a, a] phase value, the initial phase using each random number as each node; The upper bound a span of described phase value is 5≤a≤100;
(3) new node phase place more
To under the phase place substitution before each node updates, establish an equation, obtain a new phase place after this node updates:
y＝x+C1×(M-x)+C2×(x-N)
Wherein, y is the phase place after node updates; X is the phase place before node updates; C1 is the control parameter of weighing the closing speed of controlling identical community interior nodes phase place, and C2 weighs the control parameter away from speed of controlling different communities intermediate node phase place, C1, C2 (0,1] choose in scope; The average phase of all nodes that M representative and node have a fillet before renewal; The average phase of all nodes that N representative and node do not have a fillet before renewal;
(4) process and upgrade posterior nodal point phase place
If while existing phase value to be greater than the phase place of a in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is positive phase place, be that each positive node phase place multiplies each other with compression ratio r1 respectively by phase value, making phase value is that each positive node phase place is distributed between [a, a] phase value; If while there is the phase place of be less than-a of phase value in all node phase places after upgrading, choosing in renewal posterior nodal point phase value is negative phase place, be that each node phase place of bearing multiplies each other with compression ratio r2 respectively by phase value, making phase value is that each node phase place of bearing is distributed between [a, a] phase value;
(5) judge whether the phase place of upgrading posterior nodal point is stablized
Phase place by the phase place after each node updates and before upgrading is subtracted each other, obtain a difference, if this difference is less than 0, this difference is asked to absolute value, in the difference of all nodes, choose a wherein difference of difference maximum, if this maximum difference is less than threshold epsilon, 0 < ε < 1, think that the phase place of all nodes tends towards stability, enter next step, otherwise the phase place using the phase place after each node updates before this node upgrades, returns to step (3) next time;
(6) statistics subinterval node number
In the time of the phase stabilization of all nodes, [a, a] phase value is evenly divided into the subinterval that several length are len, the number of the phase place of adding up each subinterval interior nodes in this subinterval scope interior nodes;
(7) output network community division result
Subinterval interior nodes number is greater than between 0 adjacent subarea and is divided into one group, in all subintervals in this group, search for the maximum of subinterval node number, if this maximum is greater than threshold value T, 1≤T≤5, the community that in this group, node corresponding to all subintervals is network, otherwise, the overlapping nodes that in this group, node corresponding to all subintervals is network.
2. the overlapping community network detection method based on automatic phase transformation cluster according to claim 1, it is characterized in that, the generation method of the network adjacent matrix described in step (1) is, from network, choose arbitrarily two nodes, judge between these two nodes and whether have fillet, if exist, element corresponding to adjacency matrix generating is 1, otherwise is 0.
3. the overlapping community network detection method based on automatic phase transformation cluster according to claim 1, it is characterized in that, described compression ratio r1 and the r2 of step (4) obtains according to the following formula: compression ratio r1=a/b, compression ratio r2=-a/c, wherein, a is the upper bound of phase value, and b is the maximum phase in all node phase places after upgrading, and c is the minimum phase in all node phase places after upgrading.
4. the overlapping community network detection method based on automatic phase transformation cluster according to claim 1, is characterized in that, the span of the length l en in the described each subinterval of step (6) is 1≤len≤5.
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| CN103475539B (en) * | 2013-09-01 | 2016-05-25 | 西安电子科技大学 | Symbolic network community detection method based on oscillator phase synchronization |
| CN103500168B (en) * | 2013-09-02 | 2017-03-15 | 中国矿业大学 | A kind of overlap complex network community discovery method and system based on Topology Potential |
| CN105574541A (en) * | 2015-12-14 | 2016-05-11 | 天云融创数据科技（北京）有限公司 | Compactness sorting based network community discovery method |
| CN106055568B (en) * | 2016-05-18 | 2019-06-28 | 安徽大学 | A kind of automatic group technology of friend of the social networks based on single step addition group |
| CN107153713B (en) * | 2017-05-27 | 2018-02-23 | 合肥工业大学 | Overlapping community detection method and system based on similitude between node in social networks |
| CN107391832A (en) * | 2017-07-15 | 2017-11-24 | 西安电子科技大学 | The method for realizing network reconfiguration is accurately matched using a step phase iterative data |
| CN110535681B (en) * | 2019-07-18 | 2021-04-27 | 西安电子科技大学 | Open computing language OpenCL parallel-based overlapping community detection method |
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