CN109145178A - A kind of relational graph processing method and processing device - Google Patents
A kind of relational graph processing method and processing device Download PDFInfo
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- CN109145178A CN109145178A CN201710459378.1A CN201710459378A CN109145178A CN 109145178 A CN109145178 A CN 109145178A CN 201710459378 A CN201710459378 A CN 201710459378A CN 109145178 A CN109145178 A CN 109145178A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9538—Presentation of query results
Abstract
This application discloses a kind of relational graph processing method and processing devices, comprising: determines the multiple cores node in relational graph to be simplified, the dummy node which is constituted for the node in relational graph to be simplified or the cluster in relational graph；Obtain multiple incidence relations between each core node；Similarity calculation is carried out to multiple incidence relations between each core node, polymerization obtains the virtual associated relationship between each core node, using obtained virtual associated relationship as the relationship between core node in relational graph to be simplified.The application merges similar relationship, to take out new virtual corresponding relationship, so that complex relationship figure be simplified, highlights trunk train of thought using the similitude between the indirect relation in relational graph between core node or cluster.
Description
Technical field
This application involves diagram data processing technique, espespecially a kind of relational graph processing method and processing device.
Background technique
With the rapid expanding of internet data, many big and complicated diagram datas are all produced in many fields, such as
Social networks etc..It is all to start with being simplified from node in the prior art to simplify the complex relationship figure of this diagram data,
Common method has: being polymerize using the similitude between node, to reach the simplification to complex relationship figure；Or it cuts
Unrelated leaf node in complex relationship figure.
Wherein, start with from node the method being polymerize, mainly the identical relationship of data type is merged to reach
To the purpose for simplifying complex relationship figure.It on the one hand is to start with being simplified from node, for complicated relational graph, since node is numerous
It is more, it implements inevitable time-consuming and laborious；On the other hand, it is merged according only to data type, association cannot be embodied well
Two nodes between relationship.
The method of above two the relevant technologies, although core node in complex relationship figure or cluster can be allowed more prominent
Out, more effective particularly with the relatively simple diagram data of indirect relation between core backbone.But for core backbone it
Between relationship complexity complex relationship figure, the simplification effect of these methods is with regard to barely satisfactory.
Summary of the invention
It in order to solve the above-mentioned technical problem, can will be complicated this application provides a kind of relational graph processing method and processing device
Relational graph is simplified, related prominent trunk train of thought.
In order to reach the application purpose, this application provides a kind of relational graph processing methods, comprising:
Determine that the multiple cores node in relational graph to be simplified, the core node are the node in relational graph to be simplified
Or the dummy node that the cluster in relational graph is constituted；
Obtain multiple incidence relations between each core node；
Similarity calculation is carried out to multiple incidence relations between each core node, polymerization obtains between each core node
Virtual associated relationship, using obtained virtual associated relationship as the relationship between core node in relational graph to be simplified.
Optionally, the method also includes: the corresponding virtual associated relationship stored after the polymerization with before described polymerize
Incidence relation.
Optionally, the method also includes virtual associated relationships after triggering the polymerization, according to the virtual associated
Incidence relation belonging to relationship is corresponding, the virtual associated relationship after selected polymerization is unfolded.
Optionally, the virtual associated relationship after the selected polymerization of the expansion includes:
The incidence relation before the corresponding all polymerizations of virtual associated relationship after reading the polymerization, and show reading
The incidence relation arrived.
Optionally, multiple incidence relations between each core node carry out similarity calculation, and polymerization obtains each core
Virtual associated relationship between heart node includes:
The similitude of the incidence relation is calculated by the relationship of different dimensions and is polymerize to obtain the virtual associated
Relationship.
Optionally, the different dimensions include following any combination: time dimension, attribute of a relation dimension, behavior pattern dimension
Degree.
Present invention also provides a kind of implementation relation map devices, comprising: division module obtains module, aggregation module；Its
In,
Division module, for determining the multiple cores node in relational graph to be simplified, the core node is wait simplify
The dummy node that the cluster in node or relational graph in relational graph is constituted；
Module is obtained, for obtaining multiple incidence relations between each core node；
Aggregation module, for carrying out similarity calculation to multiple incidence relations between each core node, polymerization obtains each
Virtual associated relationship between core node, using obtained virtual associated relationship as core node in relational graph to be simplified it
Between relationship.
Optionally, described device further include:
Memory module, for corresponding to the virtual associated relationship after storing the polymerization and the incidence relation before described polymerize；
Module is unfolded, it is corresponding according to the virtual associated relationship for virtual associated relationship after triggering the polymerization
Affiliated incidence relation, the virtual associated relationship after selected polymerization is unfolded.
Optionally, the expansion module is specifically used for: the corresponding all institutes of virtual associated relationship after reading the polymerization
Incidence relation before stating polymerization, and show the incidence relation read.
The application provides a kind of relational graph processing unit, including memory and processor again, wherein stores in memory
There is following executable instruction: determining that the multiple cores node in relational graph to be simplified, the core node are relationship to be simplified
The dummy node that the cluster in node or relational graph in figure is constituted；Obtain multiple incidence relations between each core node；
Similarity calculation is carried out to multiple incidence relations between each core node, polymerization obtains the virtual associated between each core node
Relationship, using obtained virtual associated relationship as the relationship between core node in relational graph to be simplified.
Scheme provided by the present application comprises determining that the multiple cores node in relational graph to be simplified, the core node are
The dummy node that the cluster in node or relational graph in relational graph to be simplified is constituted；It obtains more between each core node
A incidence relation；To between each core node multiple incidence relations carry out similarity calculation, polymerization obtain each core node it
Between virtual associated relationship, using obtained virtual associated relationship as the relationship between core node in relational graph to be simplified.
The application merges similar relationship using the similitude between the incidence relation between core node in relational graph, with
New virtual associated relationship is taken out, so that complex relationship figure be simplified, highlights trunk train of thought.
Further, present invention also provides the method for the independent rail after expansion polymerization, the part in relational graph is realized
Information expansion, so that the relationship between two nodes or between two clusters is stripped out from complex relationship figure, is analyzed
It is facilitated come also apparent.
Other features and advantage will illustrate in the following description, also, partly become from specification
It obtains it is clear that being understood and implementing the application.The purpose of the application and other advantages can be by specifications, right
Specifically noted structure is achieved and obtained in claim and attached drawing.
Detailed description of the invention
Attached drawing is used to provide to further understand technical scheme, and constitutes part of specification, with this
The embodiment of application is used to explain the technical solution of the application together, does not constitute the limitation to technical scheme.
Fig. 1 is the flow chart of the application relational graph processing method；
Fig. 2 (a) is the schematic diagram that complex relationship figure to be simplified is divided into the embodiment of several clusters in the application；
It by complex relationship figure to be simplified is the signal for being divided into the embodiment of several core nodes that Fig. 2 (b), which is in the application,
Figure；
Fig. 3 is the schematic diagram for the embodiment that the application polymerize similar independent rail；
Fig. 4 is the schematic diagram of the embodiment of the simplified relational graph of the application；
Fig. 5 is the schematic diagram of the embodiment after the application polymerize the independent rail in Fig. 4；
Fig. 6 is the schematic diagram for the embodiment that certain independent rail after polymerizeing in Fig. 5 is unfolded in the application；
Fig. 7 is the composed structure schematic diagram for the device that the application implementation relation figure simplifies.
Specific embodiment
For the purposes, technical schemes and advantages of the application are more clearly understood, below in conjunction with attached drawing to the application
Embodiment be described in detail.It should be noted that in the absence of conflict, in the embodiment and embodiment in the application
Feature can mutual any combination.
In a typical configuration of this application, calculating equipment includes one or more processors (CPU), input/output
Interface, network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include non-temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
Step shown in the flowchart of the accompanying drawings can be in a computer system such as a set of computer executable instructions
It executes.Also, although logical order is shown in flow charts, and it in some cases, can be to be different from herein suitable
Sequence executes shown or described step.
When diagram data is bigger, the connection between core node or cluster shown on complex relationship figure needs logical
Excessive layer indirect relation can just associate.In order to which complex relationship figure is simplified, related prominent trunk train of thought, this Shen
A kind of relational graph processing method please be provide, as shown in Figure 1, comprising the following steps:
Step 100: determining the multiple cores node in relational graph to be simplified.
Wherein, the virtual section that core node is constituted for the node in relational graph to be simplified or the cluster in relational graph
Point.
In other words, this step seeks to relational graph to be simplified being divided into several characteristic areas.Characteristic area can be with
It is several zonules being made of core node, is also possible to several clusters marked off.Specifically, relational graph to be simplified is found out
In several core nodes or relational graph to be simplified is divided into several clusters.
Wherein, relational graph is divided into several clusters has many methods, such as: community discovery method such as LPA (Label
Propagation Algorithm), SLPA (Speaker-listener Label Propagation Algorithm) etc.；
For another example: overlapping community discovery algorithm such as BMLPA (the Multiplex Ligation-dependent propagated based on balanced multi-tag
Probe Amplification)；For another example: community detecting algorithm such as Fast Unfolding etc..
Wherein, the method for calculating core node can include but is not limited to: pagerank, k-core etc..Wherein,
Pagerank is a kind of algorithm of assessment webpage significance level of google invention, and principle can also be used to judge relational network
The center degree at midpoint；K-core is the algorithm of the center degree at another evaluation relations network Europe midpoint.
As shown in Fig. 2 (a), illustrates relational graph to be simplified and be divided into tri- regions cluster A, cluster B and cluster C, such as
Shown in Fig. 2 (b), it is shown that from relational graph to be simplified calculated core node A, core node B and core node C.
Step 101: obtaining multiple incidence relations between each core node.
As shown in Fig. 2 (a) or Fig. 2 (b), by taking vertex A and vertex B as an example, core node A and core node B or cluster
It is between A and cluster B, without public internal vertex path mutually be known as independent rail.Independent rail express two core nodes or
Incidence relation between person's cluster, describes how two core backbone associate, that is, incidence relation information.Such as
Shown in Fig. 2 (a) or Fig. 2 (b), the line segment that two-wire indicates is the independent rail between cluster or core node.Wherein, one solely
Number of nodes included in vertical rail is known as the degree of this independent rail, is indicated with N.In practical application, nearlyr relationship is often paid close attention to
Independent rail, that is, the degree lesser independent rail, such as N≤2 of independent rail etc..The value of N depends on application scenarios, such as:
Colleague scene in, rule of thumb the value of N take 2 be it is proper, the feelings of a coastiong may be multiplied altogether by covering two people here
Condition (N=1) also contemplated the situation (N=2) that user reaches by different train numbers the same place in the same period；For another example:
In the scene lived together, the value of N is 1 proper, stays in one place such as hotel etc. together because living together and often represent.
Independent rail how is obtained, there is many algorithms, the protection that specific algorithm is not intended to limit the present invention in graph theory
Range, which is not described herein again.
Step 102: similarity calculation being carried out to multiple incidence relations between each core node, polymerization obtains each core section
Virtual associated relationship between point, using obtained virtual associated relationship as the pass between core node in relational graph to be simplified
System.
In this step, the similitude of incidence relation can be calculated by the relationship of different dimensions and is polymerize, such as: when
Between dimension, that is, similitude be the same period, and/or attribute of a relation dimension i.e. similitude be same attribute, and/or behavior pattern dimension i.e.
Similitude is same behavior.
Wherein, the relationship type for calculating similitude independent rail according to expressed by incidence relation of incidence relation carries out
Similitude judges, such as two independent rails between independent rail A and independent rail B are all that trip is related.It should be noted that different
The judgement of business scenario similitude be it is different, depending on different strategies.It is to hold based on technical solution provided by the present application
Intelligible, specific strategy is not used to limit the protection scope of the application, and which is not described herein again.
In the application, it can be polymerize according to the combination of the similitude of three calculated incidence relations of dimension, such as
It polymerize the indirect relation with belonging to property of period, indirect relation that polymerization is with period colleague, etc..
Fig. 3 is the schematic diagram for the embodiment that the application polymerize similar independent rail, as shown in figure 3, being respectively from top to bottom
According to same attribute, with the merging of behavior and the similarity relation described with three aspects of period.
Such as: such as first merging mode in Fig. 3, it is assumed that there are two independences between core node A and core node B
Rail, wherein an independent rail indicates: the equipment that IMEI is #3eedf3ed is 3443223 in core node A and core by QQ number code
Login was carried out between heart node B, another independent rail indicates: the equipment that IMEI is #3eedf3ed is by QQ number code
2222222 carried out login between core node A and core node B, and two independent rails exist to be stepped on using same equipment
The similitude of the same attribute of record, therefore it is polymerized to the independent rail of same IMEI.
For another example: such as second merging mode in Fig. 3, it is assumed that there are two independent rails between cluster A and cluster B, wherein
One independent rail indicates: 16 on March 15,14:45 or so, flight CA1232 is reached, and another independent rail indicates: 16 year March 18
Or so day 14:45, flight CA1232 is reached, and two independent rails have the similitude of the same behavior with schedule flight, therefore polymerize
For the independent rail of same schedule flight.
For another example: such as the third merging mode in Fig. 3, it is assumed that there are two independent rails between cluster A and cluster B, wherein
One independent rail indicates: 16 on March 15,14:45 or so, flight G124 is reached, and another independent rail indicates: on March 15th, 16
14:45 or so, flight MU1122 are reached, and two independent rails have the similitude of section while arrival with the period, therefore are polymerized to
The independent rail reached with the period.
When there are many similarity relation as shown in Figure 3 between core node or cluster, pass through polymerization side provided by the present application
Formula greatlies simplify the indirect relation between core node or cluster, so that the connection between core node or cluster
It is more clear.
Optionally, the application method further include:
Virtual associated relationship after storage polymerization is such as showed with independent rail and is polymerize preceding each analogous relationship relationship such as with independence
The corresponding relationship of the connection relationship of rail performance corresponds to the virtual associated relationship after storing the polymerization and the pass before described polymerize
Connection relationship.Independent rail after the side generated after each polymerization polymerize contains a drilldown field, should
Stored in drilldown field it includes similar independent rail connection.
According to the simplified relational graph of similarity combination between the application independence rail, clear displaying core node is realized
Between incidence relation.But it may still need to check certain detailed association between core node two-by-two when relationship map analysis
Relationship.Optionally, the application method further include:
According to stored corresponding relationship, the virtual associated relationship after selected polymerization is unfolded is such as with the performance of independent rail.Than
Such as, when side, that is, independent rail after some polymerization of triggering is unfolded namely user wants to check that the independent rail after which polymerization clicks on
Side where which independent rail, at this point, all sons under can read the drilldown field of the independent rail after the polymerization are independent
Then rail shows this little independent rail.
The application is using the similitude between the incidence relation in relational graph between core node or cluster, to similar relationship
Merged, to take out new virtual associated relationship, so that complex relationship figure be simplified, highlights trunk train of thought.
Further, present invention also provides the method for the independent rail after expansion polymerization, the part in relational graph is realized
Information expansion, so that the relationship between first city and two, second city core node is stripped out from complex relationship figure, analysis is got up
Also apparent to facilitate.
Look at the realization in the application to polymerization and the expansion of independent rail below with reference to one embodiment.
Fig. 4 is the schematic diagram of the embodiment of the simplified relational graph of the application, it is assumed that complex relationship figure is drawn
The characteristic area separated includes three core nodes: the city A, the city B and the city C.It is produced again between three core nodes by train
Miscellaneous indirect relation.By taking the relationship that the heavy line in Fig. 4 indicates as an example, illustrate that first and second have sat train HB4540 with the period
(first) and train HB1590 (second), there are also the independences that section while others are similar sat different trains between first and second
Rail.
Fig. 5 is the schematic diagram of the embodiment after the application polymerize the independent rail in Fig. 4, in the present embodiment, will be answered
Miscellaneous indirect relation has been abstracted into the trip relationship with the period, as shown in figure 5, the relationship between core node becomes simple clear
?.Here, the independent rail after polymerizeing and the corresponding relationship for polymerizeing preceding each similar independent rail connection relationship can be stored, as shown in figure 5,
Dotted line between first city and second city leads in the corresponding data field in the side when being the indirect relation after merging similar independent rail
Cross drilldown describe it includes all independent rails of son, corresponding relationship includes first pair between first city and second city here
It should be related to, the second corresponding relationship between the third city and second city.
Fig. 6 is the schematic diagram for the embodiment that certain independent rail after polymerizeing in Fig. 5 is unfolded in the application, it is assumed that is needed
The incidence relation between first city and second city is unfolded, as shown in fig. 6, being presented in the independent rail after polymerization according to the first corresponding relationship
In relational graph.In this way, the local message expansion in relational graph is realized, so that the pass between first city and two, second city core node
System is stripped out from complex relationship figure, analyzes also apparent facilitate.
The application also provides one kind for relational graph processing unit, includes at least memory and processor, wherein memory
In be stored with following executable instruction: determine that the multiple cores node in relational graph to be simplified, the core node are wait simplify
Relational graph in node or the dummy node that is constituted of the cluster in relational graph；Obtain multiple associations between each core node
Relationship；Similarity calculation is carried out to multiple incidence relations between each core node, polymerization obtains the void between each core node
Quasi- incidence relation, using obtained virtual associated relationship as the relationship between core node in relational graph to be simplified.
Fig. 7 is the composed structure schematic diagram for the device that the application implementation relation figure simplifies, as shown in fig. 7, including at least: being drawn
Sub-module obtains module, aggregation module；Wherein,
Division module, for determining the multiple cores node in relational graph to be simplified, the core node is wait simplify
The dummy node that the cluster in node or relational graph in relational graph is constituted；
Module is obtained, for obtaining multiple incidence relations between each core node；
Aggregation module, for carrying out similarity calculation to multiple incidence relations between each core node, polymerization obtains each
Virtual associated relationship between core node, using obtained virtual associated relationship as core node in relational graph to be simplified it
Between relationship.
Optionally, aggregation module is specifically used for: calculating the similitude of the incidence relation simultaneously by the relationship of different dimensions
It is polymerize to obtain the virtual associated relationship.
Further, the application device further include: memory module is closed for the virtual associated after the corresponding storage polymerization
It is and the incidence relation before described polymerize.
Further, the application device further include:
Module is unfolded, it is corresponding according to the virtual associated relationship for virtual associated relationship after triggering the polymerization
Affiliated incidence relation, the virtual associated relationship after selected polymerization is unfolded.
Optionally, expansion module is specifically used for: the virtual associated relationship after reading the polymerization is corresponding all described poly-
Incidence relation before conjunction, and show the incidence relation read.
The application is using the similitude between the indirect relation in relational graph between core node or cluster, to similar relationship
Merged, to take out new virtual corresponding relationship, so that complex relationship figure be simplified, highlights trunk train of thought.
Further, it present invention also provides the scheme of the paradigmatic relation information after expansion polymerization, realizes in relational graph
Local message expansion so that the relationship between first city and two, second city core node is stripped out from complex relationship figure, point
Analyse also apparent facilitate.
Although embodiment disclosed by the application is as above, the content only for ease of understanding the application and use
Embodiment is not limited to the application.Technical staff in any the application fields, is taken off not departing from the application
Under the premise of the spirit and scope of dew, any modification and variation, but the application can be carried out in the form and details of implementation
Scope of patent protection, still should be subject to the scope of the claims as defined in the appended claims.
Claims (10)
1. a kind of relational graph processing method characterized by comprising
Determine that the multiple cores node in relational graph to be simplified, the core node are node or pass in relational graph to be simplified
It is the dummy node that the cluster in figure is constituted；
Obtain multiple incidence relations between each core node；
Similarity calculation is carried out to multiple incidence relations between each core node, polymerization obtains virtual between each core node
Incidence relation, using obtained virtual associated relationship as the relationship between core node in relational graph to be simplified.
2. relational graph processing method according to claim 1, which is characterized in that the method also includes: corresponding storage institute
State the virtual associated relationship after polymerizeing and the incidence relation before described polymerize.
3. relational graph processing method according to claim 2, which is characterized in that the method also includes: described in triggering
Virtual associated relationship after polymerization, according to the corresponding affiliated incidence relation of the virtual associated relationship, after selected polymerization is unfolded
Virtual associated relationship.
4. relational graph processing method according to claim 3, which is characterized in that virtual after the selected polymerization of the expansion
Incidence relation includes:
The incidence relation before the corresponding all polymerizations of virtual associated relationship after reading the polymerization, and show and read
The incidence relation.
5. relational graph processing method according to claim 1,2 or 3, which is characterized in that described between each core node
Multiple incidence relations carry out similarity calculation, polymerizeing the virtual associated relationship that obtains between each core node includes:
The similitude of the incidence relation is calculated by the relationship of different dimensions and is polymerize to obtain the virtual associated relationship.
6. relational graph processing method according to claim 5, which is characterized in that the different dimensions include following any group
It closes: time dimension, attribute of a relation dimension, behavior pattern dimension.
7. a kind of relational graph processing unit characterized by comprising division module obtains module, aggregation module；Wherein,
Division module, for determining that the multiple cores node in relational graph to be simplified, the core node are relationship to be simplified
The dummy node that the cluster in node or relational graph in figure is constituted；
Module is obtained, for obtaining multiple incidence relations between each core node；
Aggregation module, for carrying out similarity calculation to multiple incidence relations between each core node, polymerization obtains each core
Virtual associated relationship between node, using obtained virtual associated relationship as between core node in relational graph to be simplified
Relationship.
8. relational graph processing unit according to claim 7, which is characterized in that described device further include:
Memory module, for corresponding to the virtual associated relationship after storing the polymerization and the incidence relation before described polymerize；
Module is unfolded, for virtual associated relationship after triggering the polymerization, according to the corresponding institute of the virtual associated relationship
Belong to incidence relation, the virtual associated relationship after selected polymerization is unfolded.
9. relational graph processing unit according to claim 8, which is characterized in that the expansion module is specifically used for: reading
The incidence relation before the corresponding all polymerizations of virtual associated relationship after the polymerization, and show the association read
Relationship.
10. a kind of relational graph processing unit, including memory and processor, wherein be stored with following executable finger in memory
It enables: determining that the multiple cores node in relational graph to be simplified, the core node are node or pass in relational graph to be simplified
It is the dummy node that the cluster in figure is constituted；Obtain multiple incidence relations between each core node；To each core node it
Between multiple incidence relations carry out similarity calculation, polymerization obtain the virtual associated relationship between each core node, will obtain
Virtual associated relationship as the relationship between core node in relational graph to be simplified.
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| CN111177876A (en) * | 2019-12-25 | 2020-05-19 | 支付宝(杭州)信息技术有限公司 | Community discovery method and device and electronic equipment |
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| CN105426499A (en) * | 2015-11-25 | 2016-03-23 | 成都数联铭品科技有限公司 | Implementation method of data visualization |
| CN105550307A (en) * | 2015-12-14 | 2016-05-04 | 北京锐安科技有限公司 | Method for generating net citizen identity relationship network graph |
| CN105786980A (en) * | 2016-02-14 | 2016-07-20 | 广州神马移动信息科技有限公司 | Method and apparatus for combining different examples for describing same entity and equipment |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111177876A (en) * | 2019-12-25 | 2020-05-19 | 支付宝(杭州)信息技术有限公司 | Community discovery method and device and electronic equipment |
| CN111177876B (en) * | 2019-12-25 | 2023-06-20 | 支付宝(杭州)信息技术有限公司 | Community discovery method and device and electronic equipment |
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