CN112465408A - Cooperation partner recommendation method based on future common neighbor similarity - Google Patents
Cooperation partner recommendation method based on future common neighbor similarity Download PDFInfo
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Abstract
The embodiment of the invention provides a partner recommending method based on future common neighbor similarity, which comprises the following steps: acquiring enterprises in a supply chain network and the cooperation relationship between the enterprises; establishing a corresponding node relation graph; acquiring a node to be recommended of a partner to be recommended and a related node to be examined in a node relation graph, and searching a future common neighbor node through the node to be recommended and the node to be examined; respectively calculating connection conditions and similarities between the node to be recommended and the node to be examined and all nodes, wherein all the nodes comprise the node to be recommended, the node to be examined and future common neighbor nodes; and calculating to obtain a final cooperative score between the node to be recommended and the node to be investigated according to the connection condition and the similarity, and recommending the node to be investigated to the node to be recommended according to the final cooperative score. By adopting the method, the recommendation method for judging the public neighbors can be provided, and the recommendation result is more accurate.
Description
Technical Field
The invention relates to the technical field of recommendation algorithms in complex networks, in particular to a partner recommendation method based on future mutual neighbor similarity.
Background
In the global market competition environment, the cooperation among enterprises is increasingly frequent for the survival and development in fiercely and changeful competition. The supply chain is a new management concept and enterprise operation mode, and since the end of the eighties, the ideas of 'cooperation' and 'win-win' are paid more and more attention, so that each enterprise involved can obtain more profits than before. With the rise of strategic management, the strategic partner relationship among supply chain enterprises becomes the focus of research, and the choice of partners is more important due to the importance and practicality of constructing the supply chain.
Most similarity-based recommendation algorithms predict users who may collaborate in the future by using the current public neighbors. However, according to the prediction principle of the similarity index, some nodes which do not belong to the public neighbors at present may become public neighbors in the future, and the recommended result is not accurate enough.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiment of the invention provides a partner recommending method based on the similarity of future common neighbors.
The embodiment of the invention provides a partner recommending method based on future mutual neighbor similarity, which comprises the following steps:
acquiring enterprises in a supply chain network and a cooperative relationship between the enterprises;
establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises;
acquiring a node to be recommended of a partner to be recommended in the node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined;
respectively calculating connection conditions between the node to be recommended and the node to be examined and all nodes, and respectively calculating similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and the future common neighbor node;
and calculating to obtain a final cooperative score between the node to be recommended and the node to be examined according to the connection condition and the similarity, and recommending the node to be examined to the node to be recommended according to the final cooperative score.
In one embodiment, the method further comprises:
and comparing the final cooperative score with a preset score threshold, performing descending order arrangement on the nodes to be checked corresponding to the final cooperative score larger than the score threshold according to the score size, and recommending the nodes to be recommended according to the descending order arrangement.
In one embodiment, the method further comprises:
and judging the type of the future common neighbor node according to the connection relationship between the node to be recommended and the future common neighbor node and the connection relationship between the node to be examined and the future common neighbor node.
In one embodiment, the category of the future common neighbor node includes:
a type: the node to be recommended and the future common neighbor node have a direct connection relationship, the node to be examined and the future common neighbor node do not have a direct connection relationship, and the similarity score between the node to be examined and the future common neighbor node is larger than a preset score;
b type: a direct connection relation does not exist between the node to be recommended and the future common neighbor node, the similarity score between the node to be recommended and the future common neighbor node is larger than a preset score, and the node to be examined and the future common neighbor node have a direct connection relation;
class C: the node to be recommended and the future common neighbor node do not have a direct connection relationship, the similarity score between the node to be recommended and the future common neighbor node is larger than a preset score, the node to be examined and the future common neighbor node do not have a direct connection relationship, and the similarity score between the node to be examined and the future common neighbor node is larger than a preset score.
In one embodiment, the method further comprises:
and converting the enterprises into nodes, converting the cooperation relationship among the enterprises into node connecting lines, and establishing a corresponding node relationship graph through the nodes and the node connecting lines.
In one embodiment, the method further comprises:
and searching for the node which has the node connection line and the two sections of node connection lines with the node to be recommended and the node to be examined as the future common neighbor node.
The embodiment of the invention provides a partner recommending device based on future mutual neighbor similarity, which comprises:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring enterprises in a supply chain network and the cooperative relationship among the enterprises;
the establishment module is used for establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises;
the second acquisition module is used for acquiring a node to be recommended of a partner to be recommended in the node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined;
the first calculation module is used for calculating the connection conditions between the node to be recommended and the node to be examined and all nodes, and calculating the similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and the future common neighbor node;
and the second calculation module is used for calculating a final cooperative score between the node to be recommended and the node to be examined according to the connection condition and the similarity, and recommending the node to be examined to the node to be recommended according to the final cooperative score.
In one embodiment, the apparatus further comprises:
and the recommending module is used for comparing the cooperative final score with a preset score threshold, performing descending order arrangement on the nodes to be checked corresponding to the cooperative final score larger than the score threshold according to the score size, and recommending the nodes to be recommended according to the descending order arrangement.
The embodiment of the invention provides electronic equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the partner recommending method based on the future mutual neighbor similarity.
Embodiments of the present invention provide a non-transitory computer readable storage medium having stored thereon a computer program that, when executed by a processor, performs the steps of the aforementioned method for partner recommendation based on future mutual neighbor similarity.
The partner recommending method based on the similarity of the future common neighbors obtains enterprises in a supply chain network and the cooperation relationship among the enterprises; establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises; acquiring a node to be recommended of a partner to be recommended in a node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined; respectively calculating connection conditions between the node to be recommended and the node to be examined and all nodes, and respectively calculating similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and future common neighbor nodes; and calculating to obtain a final cooperative score between the node to be recommended and the node to be investigated according to the connection condition and the similarity, and recommending the node to be investigated to the node to be recommended according to the final cooperative score. Therefore, the recommendation method for judging the public neighbors can be provided, and the recommendation result is more accurate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a method for partner recommendation based on future mutual neighbor similarity in an embodiment of the present invention;
FIG. 2 is a node relationship diagram established according to enterprises and partnerships among enterprises in an embodiment of the present invention;
FIG. 3 is a diagram illustrating the types of future common neighbor nodes in an embodiment of the present invention;
FIG. 4 is a block diagram of a partner recommender based on future mutual neighbor similarity according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flowchart of a partner recommendation method based on future mutual neighbor similarity according to an embodiment of the present invention, and as shown in fig. 1, an embodiment of the present invention provides a partner recommendation method based on future mutual neighbor similarity, including:
step S101, acquiring enterprises in the supply chain network and the cooperation relationship among the enterprises.
Specifically, the node information corresponding to the supply chain enterprise in the supply chain network and the topology structure information between the nodes are obtained, that is, the enterprise in the supply chain and the cooperation relationship between the enterprises are obtained.
And S102, establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises.
Specifically, a corresponding node relationship graph is established according to the enterprises and the cooperative relationships among the enterprises, and the node relationship graph can be as shown in fig. 2, where fig. 2 includes a node x for which a partner needs to be recommended, an arbitrary investigation object y node, and future common neighbor nodes of all x and y. The specific establishing method comprises the steps of converting enterprises into nodes, converting cooperation relations among the enterprises into node connecting lines, and establishing a corresponding node relation graph through the nodes and the node connecting lines.
Step S103, acquiring a node to be recommended of a partner to be recommended in the node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined.
Specifically, a node x for which a partner needs to be recommended and an arbitrary inspected object y node are acquired through a node relation graph, a future common neighbor node is acquired through the x node and the y node, the future common neighbor node is a neighbor node which can be recommended for the x node in the future, and the method for searching the future common neighbor node can search nodes which have a node connection line and two node connection lines with the node to be recommended and the node to be examined, namely, nodes which have a direct cooperation relationship and an indirect cooperation relationship with the x node and the y node, namely, the future common neighbor node.
In addition, the category of the future common neighbor node may also be determined according to the connection relationship between the node to be recommended and the future common neighbor node and the connection relationship between the node to be examined and the future common neighbor node, and the specific category may be classified into 3 categories, specifically as shown in fig. 3, including category a (fig. 3 (a)): a direct connection relation exists between the node (x) to be recommended and a future common neighbor node (i), a direct connection relation does not exist between the node (y) to be examined and the future common neighbor node, the similarity score between the node to be examined and the future common neighbor node is larger than a preset score, and according to the prediction principle of a similarity algorithm, the i and the y may form a link in the future; class B (fig. 3 (B)): a direct connection relation does not exist between the node to be recommended and a future common neighbor node, the similarity score between the node to be recommended and the future common neighbor node is larger than a preset score, and the node to be examined and the future common neighbor node have a direct connection relation; class C (fig. 3 (C)): the node to be recommended and the future common neighbor node do not have a direct connection relation, the similarity score between the node to be recommended and the future common neighbor node is larger than a preset score, the node to be examined and the future common neighbor node do not have a direct connection relation, and the similarity score between the node to be examined and the future common neighbor node is larger than the preset score
Step S104, respectively calculating the connection conditions between the node to be recommended and the node to be examined and all nodes, and respectively calculating the similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and the future common neighbor node.
Specifically, the connection conditions between the node to be recommended and the node to be examined and all the nodes are calculated, and the similarity between the node to be recommended and the node to be examined and all the nodes is calculated, and according to the connection conditions in fig. 2, all the nodes refer to specific calculation steps of all the nodes in fig. 2, including: calculating the connection situation separately, i.e. separately
And
i.e. the connection of node x to all nodes and the connection of node y to all nodes, in particular, when i = x or i = y,
=0，
=0，
=0，
=0, in the example of fig. 2,
= (0101000000) (connection scenario of x nodes to 9 nodes in figure 2),
=
(connection scenario of y node to 9 nodes in fig. 2), where,
representing the similarity between node x and node i calculated with the classical algorithm RA,
indicating whether node i and node y are connected,
=1 denotes that i and y are connected,
=0 indicates that i and y are not connected,
is the similarity of i and y calculated by RA,
is used for characterizing whether x and i are connected or not,
wherein
A set of neighbor nodes representing node x,
representing the degree of node z. After the connection condition is obtained through calculation, the similarity between all the nodes is calculated respectively, namely the similarity is calculated respectively
And
i.e., the similarity of node x to all nodes and the similarity of node y to all nodes, in the example of fig. 2,
= 
，
= 
。
and S105, calculating to obtain a final cooperative score between the node to be recommended and the node to be examined according to the connection condition and the similarity, and recommending the node to be examined to the node to be recommended according to the final cooperative score.
Specifically, the final score of cooperation between the node to be recommended and the node to be investigated is calculated according to the calculated connection condition and the similarity, and according to fig. 2, the specific calculation method may be to calculate the final score of cooperation between the target nodes x and y based on the future mutual neighbor similarity model
，
Wherein the content of the first and second substances,
and
is a free parameter, and respectively adjusts the weights of the current common neighbor and the future common neighbor when
0 and
when =0, the model only considers the current common neighbors when
=0 and
0, only future co-neighbors are considered, and, in general,
，
wherein
A set of neighbor nodes representing node x,
and representing the degree of the node x, and recommending the node to be checked to the node to be recommended according to the final cooperative score after calculating the final cooperative score between the target node x and the target node y.
In addition, calculating the cooperation final scores of all the nodes to be checked (all the y nodes) and the nodes to be recommended (the x nodes), comparing the cooperation final scores with a preset score threshold, arranging the nodes to be checked corresponding to the cooperation final scores larger than the score threshold in a descending order according to the score size, and recommending the nodes to be recommended according to the descending order. The recommended number of the nodes to be checked can also recommend a preset number of the nodes to be recommended to the nodes to be recommended according to the setting of the nodes to be recommended.
The embodiment of the invention provides a partner recommendation method based on the similarity of future common neighbors, which is used for acquiring enterprises in a supply chain network and the cooperative relationship among the enterprises; establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises; acquiring a node to be recommended of a partner to be recommended in a node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined; respectively calculating connection conditions between the node to be recommended and the node to be examined and all nodes, and respectively calculating similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and future common neighbor nodes; and calculating to obtain a final cooperative score between the node to be recommended and the node to be investigated according to the connection condition and the similarity, and recommending the node to be investigated to the node to be recommended according to the final cooperative score. Therefore, the recommendation method for judging the public neighbors can be provided, and the recommendation result is more accurate.
Fig. 4 is a partner recommending apparatus based on future mutual neighbor similarity according to an embodiment of the present invention, including: a first obtaining module 201, a establishing module 202, a second obtaining module 203, a first calculating module 204 and a second calculating module 205, wherein:
the first acquiring module 201 is configured to acquire enterprises in the supply chain network and a collaboration between the enterprises.
An establishing module 202, configured to establish a corresponding node relationship graph according to the enterprises and the cooperative relationships between the enterprises.
A second obtaining module 203, configured to obtain a node to be recommended of a partner to be recommended in the node relationship diagram, obtain a relevant node to be examined according to the node to be recommended, and search a future common neighbor node through the node to be recommended and the node to be examined.
The first calculating module 204 is configured to calculate connection conditions between the node to be recommended and the node to be examined and all nodes, and calculate similarities between the node to be recommended and the node to be examined and all nodes, where all nodes include the node to be recommended, the node to be examined, and the future common neighbor node.
The second calculating module 205 is configured to calculate a final cooperative score between the node to be recommended and the node to be examined according to the connection condition and the similarity, and recommend the node to be examined to the node to be recommended according to the final cooperative score.
In one embodiment, the apparatus may further comprise:
and the recommending module is used for comparing the cooperative final score with a preset score threshold, performing descending order arrangement on the nodes to be checked corresponding to the cooperative final score larger than the score threshold according to the score size, and recommending the nodes to be recommended according to the descending order arrangement.
In one embodiment, the apparatus may further comprise:
and the judging module is used for judging the type of the future common neighbor node according to the connection relationship between the node to be recommended and the future common neighbor node and the connection relationship between the node to be examined and the future common neighbor node.
In one embodiment, the apparatus may further comprise:
and the second establishing module is used for converting the enterprises into nodes, converting the cooperation relationship among the enterprises into node connecting lines, and establishing a corresponding node relationship graph through the nodes and the node connecting lines.
In one embodiment, the apparatus may further comprise:
and the searching module is used for searching the node which has the node connecting line and the two sections of node connecting lines with the node to be recommended and the node to be inspected, and the node is the future common neighbor node.
For specific definition of the partner recommending apparatus based on the future mutual neighbor similarity, reference may be made to the above definition of the partner recommending method based on the future mutual neighbor similarity, and details thereof are not repeated here. The various modules in the future mutual neighbor similarity based partner recommendation device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
Fig. 5 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 5: a processor (processor)301, a memory (memory)302, a communication Interface (Communications Interface)303 and a communication bus 304, wherein the processor 301, the memory 302 and the communication Interface 303 complete communication with each other through the communication bus 304. The processor 301 may call logic instructions in the memory 302 to perform the following method: acquiring enterprises in a supply chain network and the cooperation relationship between the enterprises; establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises; acquiring a node to be recommended of a partner to be recommended in a node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined; respectively calculating connection conditions between the node to be recommended and the node to be examined and all nodes, and respectively calculating similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and future common neighbor nodes; and calculating to obtain a final cooperative score between the node to be recommended and the node to be investigated according to the connection condition and the similarity, and recommending the node to be investigated to the node to be recommended according to the final cooperative score.
Furthermore, the logic instructions in the memory 302 may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the transmission method provided in the foregoing embodiments when executed by a processor, and for example, the method includes: acquiring enterprises in a supply chain network and the cooperation relationship between the enterprises; establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises; acquiring a node to be recommended of a partner to be recommended in a node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined; respectively calculating connection conditions between the node to be recommended and the node to be examined and all nodes, and respectively calculating similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and future common neighbor nodes; and calculating to obtain a final cooperative score between the node to be recommended and the node to be investigated according to the connection condition and the similarity, and recommending the node to be investigated to the node to be recommended according to the final cooperative score.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for partner recommendation based on future mutual neighbor similarity, comprising:
acquiring enterprises in a supply chain network and a cooperative relationship between the enterprises;
establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises;
acquiring a node to be recommended of a partner to be recommended in the node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined;
respectively calculating connection conditions between the node to be recommended and the node to be examined and all nodes, and respectively calculating similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and the future common neighbor node;
and calculating to obtain a final cooperative score between the node to be recommended and the node to be examined according to the connection condition and the similarity, and recommending the node to be examined to the node to be recommended according to the final cooperative score.
2. The method of claim 1, wherein recommending the node to be investigated to the node to be recommended according to a final cooperative score comprises:
and comparing the final cooperative score with a preset score threshold, performing descending order arrangement on the nodes to be checked corresponding to the final cooperative score larger than the score threshold according to the score size, and recommending the nodes to be recommended according to the descending order arrangement.
3. The method of claim 1, wherein after searching for a future common neighbor node through the node to be recommended and the node to be investigated, the method comprises:
and judging the type of the future common neighbor node according to the connection relationship between the node to be recommended and the future common neighbor node and the connection relationship between the node to be examined and the future common neighbor node.
4. The method of claim 3, wherein the category of the future mutual neighbor nodes comprises:
a type: the node to be recommended and the future common neighbor node have a direct connection relationship, the node to be examined and the future common neighbor node do not have a direct connection relationship, and the similarity score between the node to be examined and the future common neighbor node is larger than a preset score;
b type: a direct connection relation does not exist between the node to be recommended and the future common neighbor node, the similarity score between the node to be recommended and the future common neighbor node is larger than a preset score, and the node to be examined and the future common neighbor node have a direct connection relation;
class C: the node to be recommended and the future common neighbor node do not have a direct connection relationship, the similarity score between the node to be recommended and the future common neighbor node is larger than a preset score, the node to be examined and the future common neighbor node do not have a direct connection relationship, and the similarity score between the node to be examined and the future common neighbor node is larger than a preset score.
5. The method of claim 1, wherein the establishing a node relationship graph according to the enterprises and the partnerships among the enterprises comprises:
and converting the enterprises into nodes, converting the cooperation relationship among the enterprises into node connecting lines, and establishing a corresponding node relationship graph through the nodes and the node connecting lines.
6. The method of claim 5, wherein the searching for the future common neighbor node through the node to be recommended and the node to be investigated comprises:
and searching for the node which has the node connection line and the two sections of node connection lines with the node to be recommended and the node to be examined as the future common neighbor node.
7. A partner recommendation apparatus based on future mutual neighbor similarity, the apparatus comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring enterprises in a supply chain network and the cooperative relationship among the enterprises;
the establishment module is used for establishing a corresponding node relation graph according to the enterprises and the cooperation relation among the enterprises;
the second acquisition module is used for acquiring a node to be recommended of a partner to be recommended in the node relation graph, acquiring a related node to be examined according to the node to be recommended, and searching a future common neighbor node through the node to be recommended and the node to be examined;
the first calculation module is used for calculating the connection conditions between the node to be recommended and the node to be examined and all nodes, and calculating the similarity between the node to be recommended and the node to be examined and all nodes, wherein all nodes comprise the node to be recommended, the node to be examined and the future common neighbor node;
and the second calculation module is used for calculating a final cooperative score between the node to be recommended and the node to be examined according to the connection condition and the similarity, and recommending the node to be examined to the node to be recommended according to the final cooperative score.
8. The future mutual neighbor similarity-based partner recommendation device according to claim 7, further comprising:
and the recommending module is used for comparing the cooperative final score with a preset score threshold, performing descending order arrangement on the nodes to be checked corresponding to the cooperative final score larger than the score threshold according to the score size, and recommending the nodes to be recommended according to the descending order arrangement.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the future mutual neighbor similarity based partner recommendation method of any of claims 1 to 6.
10. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, performs the steps of the future mutual neighbor similarity based partner recommendation method of any of claims 1 to 6.
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