CN113115200B - User relationship identification method and device and computing equipment - Google Patents
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Abstract
The embodiment of the invention relates to the technical field of data processing, and discloses a user relationship identification method, a user relationship identification device and computing equipment. Wherein, the method comprises the following steps: acquiring communication data of a user; determining a user relationship pair between the user and an associated user of the user according to the communication data; acquiring the position data of the user and the position data of the associated user; determining a reliable relation pair in the user relation pair according to the position data of the user and the position data of the associated user; determining a relationship set of the user according to the reliable relationship pair; and determining the relationship between the user and other users in the relationship set of the user according to the portrait information of the user and portrait information of other users in the relationship set of the user. Through the mode, the embodiment of the invention can achieve the effect of higher identification accuracy of the user relationship.
Description
Technical Field
The embodiment of the invention relates to the technical field of data processing, in particular to a user relationship identification method and device and computing equipment.
Background
With the rapid development of communication technology, online communication has become a main communication mode among users, so that a social relationship network of the users is obtained through online behaviors of the users, and the method has great value for understanding the user behaviors and the social relationships of the users. For example, based on the social relationship of the user, accurate marketing and the like are realized.
At present, a user relationship identification method generally identifies relationships among users based on conversation data of the users, and the method is difficult to distinguish relationships such as relatives and friends, and has low accuracy in identifying the intimacy degree of the relationships.
Disclosure of Invention
In view of the foregoing problems, embodiments of the present invention provide a method, an apparatus, and a computing device for identifying a user relationship, which can achieve an effect of high accuracy in identifying a user relationship.
According to an aspect of an embodiment of the present invention, a method for identifying a user relationship is provided, where the method includes: acquiring communication data of a user; determining a user relationship pair between the user and an associated user of the user according to the communication data; acquiring the position data of the user and the position data of the associated user; determining a reliable relation pair in the user relation pair according to the position data of the user and the position data of the associated user; determining a relationship set of the user according to the reliable relationship pair; and determining the relationship between the user and other users in the relationship set of the user according to the portrait information of the user and portrait information of other users in the relationship set of the user.
In an optional manner, the determining a reliable relationship pair in the user relationship pair according to the location data of the user and the location data of the associated user further includes: determining whether a relation user which appears at the same position with the user at the same time exists in the associated users or not according to the position data of the user and the position data of the associated users; and when a relationship user which appears at the same position at the same time as the user exists, determining the user relationship pair of the relationship user as the reliable relationship pair.
In an optional manner, the method further comprises: coding the user and the associated user, and acquiring a user code of the user and a user code of the associated user;
then, the determining a relationship set of the user according to the reliable relationship pair further includes: obtaining a first reliable relation pair in the reliable relation pair, wherein the first reliable relation pair comprises the user and a first user in the associated users; comparing the user code of the user with the user code of the first user; taking the user code of the user and the user code of the first user which is smaller as the identifier of the first reliable relation pair; obtaining a second reliable relation pair in the reliable relation pair, wherein the second reliable relation pair comprises the user and a second user in the associated users; comparing the user code of the user with the user code of the second user; taking the smaller user code of the user and the user code of the second user as the identifier of the second reliable relation pair; and if the identification of the first reliable relationship pair is the same as the identification of the second reliable relationship pair, taking the first user and the second user as the subset of the relationship set of the users.
In an optional manner, the determining the relationship set of the user according to the reliable relationship pair further includes: determining the weight of the user relationship pair according to the communication data; determining the weight of the reliable relation pair according to the weight of the user relation pair; and determining the relationship set of the user according to the weight of the reliable relationship pair.
In an optional manner, the determining the relationship set of the user according to the weights of the reliable relationship pairs further includes: when the user in the relationship set of the user appears in other relationship sets, determining that the user appearing in other relationship sets is a repeated user; calculating the average weight of the reliable relation pairs in the relation set of the user and the average weight of other reliable relation pairs in the other relation sets; and if the average weight of the reliable relationship pairs in the relationship set of the user is smaller than the average weight of the other reliable relationship pairs in the other relationship set, removing the repeated user from the relationship set of the user.
In an optional manner, the method further comprises: and when the user relationship pair has a user which is not divided into any relationship set, adding the user which is not divided into any relationship set into the relationship set of the user.
In an optional manner, the determining, according to the portrait information of the user and portrait information of other users in the relationship set of the user, a relationship between the user and other users in the relationship set of the user further includes: acquiring night position information of the user and night position information of other users; and determining the relationship between the user and other users in the relationship set of the user according to the night position information of the user, the night position information of other users, the portrait information of the user and the portrait information of other users.
According to another aspect of the embodiments of the present invention, there is provided a user relationship identifying apparatus, including: the communication data acquisition module is used for acquiring communication data of a user; a relation pair determining module, configured to determine a user relation pair between the user and an associated user of the user according to the communication data; a location data acquisition module for acquiring location data of the user and location data of the associated user; a reliable relationship pair determining module, configured to determine a reliable relationship pair in the user relationship pair according to the location data of the user and the location data of the associated user; a relationship set determining module, configured to determine a relationship set of the user according to the reliable relationship pair; and the relationship type determining module is used for determining the relationship between the user and other users in the relationship set of the user according to the portrait information of the user and the portrait information of other users in the relationship set of the user.
According to still another aspect of an embodiment of the present invention, there is provided a computing device including: a processor, a memory, and a communication interface, the processor, the memory, and the communication interface in communication with each other; the memory is used for storing at least one executable instruction which causes the processor to execute the operation of the user relationship identification method.
According to another aspect of the embodiments of the present invention, there is provided a computer-readable storage medium, in which at least one executable instruction is stored, and the executable instruction causes a processor to execute the user relationship identification method as described above.
According to the embodiment of the invention, the communication data of the user is acquired, the user relationship pair is determined between the user and the associated user of the user according to the communication data, the position data of the user and the position data of the associated user are acquired, the reliable relationship pair is determined in the user relationship pair according to the position data of the user and the position data of the associated user, the relationship set of the user is determined according to the reliable relationship pair, the relationship between the user and other users in the relationship set of the user is determined according to the portrait information of the user and the portrait information of other users in the relationship set of the user, and the interaction behavior of the user and the position data are combined, so that the problems of low coverage rate and low accuracy rate of single data are solved, and the effect of high identification accuracy rate of the user relationship can be achieved.
The foregoing description is only an overview of the technical solutions of the embodiments of the present invention, and the embodiments of the present invention can be implemented according to the content of the description in order to make the technical means of the embodiments of the present invention more clearly understood, and the detailed description of the present invention is provided below in order to make the foregoing and other objects, features, and advantages of the embodiments of the present invention more clearly understandable.
Drawings
Various additional advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart illustrating a user relationship identification method according to an embodiment of the present invention;
FIG. 2 shows a flowchart of step 140 in FIG. 1;
FIG. 3 shows a flowchart of step 160 in FIG. 1;
FIG. 4 is a flow chart illustrating a method for identifying user relationships according to another embodiment of the present invention;
FIG. 5 shows a flowchart of step 206 in FIG. 4;
FIG. 6 shows a flowchart of step 209 of FIG. 4;
FIG. 7 is a flowchart illustrating a user relationship identification method according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a computing device provided in an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
At present, a user relationship identification method generally identifies relationships among users based on call data of the users, and the method is difficult to distinguish relationships such as relatives and friends, and has low accuracy in identifying the intimacy degree of the relationships.
Based on this, the embodiment of the invention provides a user relationship identification method, a user relationship identification device and a computing device, which can achieve the effect of higher user relationship identification accuracy.
Specifically, the embodiments of the present invention will be further explained below with reference to the drawings.
It should be understood that the following examples are provided by way of illustration and are not intended to limit the invention in any way to the particular embodiment disclosed.
Fig. 1 shows a flowchart of a user relationship identification method according to an embodiment of the present invention. The method may be applied to a computing device. As shown in fig. 1, the method comprises the steps of:
and step 110, obtaining communication data of the user.
The communication data of the user may include real-time communication data and historical communication data, the real-time communication data refers to one or more of call data, video data, short message data, voice data and the like of the user in real time, and the historical communication data refers to one or more of call data, video data, short message data, voice data and the like in the historical record.
The associated user of the user refers to a user related to the user, that is, a user having a communication behavior with the user. The user relationship pair is composed of two persons of a user and an associated user, and the number of the user relationship pair can be one pair or a plurality of pairs. The user relationship pair may be updated within a preset time, for example, the user relationship pair is updated once a month.
According to the communication data, a user relationship pair is determined between the user and the associated user of the user, which may specifically be: the method comprises the steps of obtaining an object pointed by communication data of a user, determining the object pointed by the communication data of the user as an associated user, and determining a user relationship pair between the user and the associated user of the user. For example, if the communication data acquired from the user a is: if the user A and the user B make a telephone call, the user A and the user C, D make a short message, and the user A and the user E, F make a voice, the associated user is B, C, D, E, F, and the user relationship pair is determined as follows: A-B, A-C, A-D, A-E, A-F.
The location data may include one or more of base station signaling data, measurement Report (MR) data, GPRS data, and OTT (Over The Top) data. Some OTT service providers provide positioning and navigation services for users, and if the APP has a situation that the position information is reported in a plaintext, longitude and latitude information can be extracted to describe the movement track of the users. The OTT data can be acquired from the core network side through a probe. Outdoor positioning can be carried out through base station signaling data, MR data and GPRS data, and indoor positioning can be carried out through OTT data and MR data.
The reliable relation pair refers to a relation pair including associated users who appear at the same time and the same place as the user. The reliability of the user relationship pair is improved by determining the reliable relationship pair, so that the accuracy of user relationship identification is improved.
Specifically, as shown in fig. 2, step 140 includes:
and 142, if so, determining the user relationship pair of the relationship user as a reliable relationship pair.
The behavior track data of the user in a time period can be determined according to the position data, so that whether the user and the associated user appear at the same place at the same time or not is judged according to the track data of the user and the track data of the associated user, and if the associated user and the user appear at the same place at the same time, the associated user is determined as the related user.
The selection criteria of the user action point can be as shown in table 1.
TABLE 1
In table 1, the number of sampling points was 1 in the time period of 8 hours-11 hours on weekdays, and a stay of 2 hours indicated that one user was present at a certain place within 2 hours of 8 hours-11 hours, the number of sampling points was 2 in the time period of 19 hours-22 hours on weekdays, and a stay of 1 hour indicated that two users were present at a certain same place within 1 hour of 19 hours-22 hours.
Wherein, the user relationship pair of the user with relationship is determined as a reliable relationship pair, for example, the user relationship pair is assumed as: A-B, A-C, A-D, A-E, A-F, determining B, C, E as the relationship user, the reliable relationship pair is A-B, A-C, A-E.
And 150, determining a relationship set of the user according to the reliable relationship pair.
The relationship set of the user comprises the user and the user closely related to the user. Determining a relationship set of the user according to the reliable relationship pair, which may specifically be: and determining the total number of the relation users in the reliable relation pairs, directly taking the relation users as the subset of the relation set of the users if the total number of the relation users is less than or equal to a preset threshold value, and taking the relation users as the subset of the relation set of the users first and then further processing the relation users if the total number of the relation users is greater than the preset threshold value.
And step 160, determining the relationship between the user and other users in the relationship set of the user according to the portrait information of the user and the portrait information of other users in the relationship set of the user.
The portrait information can be characteristic information of the user obtained according to service registration information, internet surfing record information and service use information of the user, and is used for assisting in judging the social identity of the user. The service registration information is real-name information of the user, and the name and the age of the user can be acquired according to the real-name information of the user. The internet record information can be a flow use record, and application software frequently used by the user can be determined according to the flow use record. The service usage information may be information of a service transacted by the user, and the like. For example, if it is acquired that the user a is 25 years old and frequently appears in school on working days, it is determined that the social identity of the user is a teacher.
The relationship between the user and other users in the relationship set of the user may include: family relationships, friendships, coworkers, and so on. Specifically, as shown in fig. 3, step 160 may include:
and step 162, determining the relationship between the user and other users in the relationship set of the user according to the night position information of the user, the night position information of other users, the portrait information of the user and the portrait information of other users.
The night position information refers to position information within a preset night time, and the preset night time can be from 22 o 'clock to 7 o' clock of the next day. The night location information can be obtained by analyzing the location data. In this embodiment, the relationship between the user and the other users in the relationship set of the user is determined according to the night position information of the user, the night position information of the other users, the portrait information of the user, and the portrait information of the other users, which may be specifically: if the number of days in which the night position information of the user is the same as the night position information of other users exceeds a preset number of days threshold value and the difference between the age of the user and the age of one of the other users exceeds a preset age difference, determining that the relationship between the user and the other users in the relationship set of the user is a family relationship; and if the fact that the number of days in which the night position information of the user is the same as the night position information of other users exceeds a preset number of days threshold value and the difference between the age of the user and the age of any other user does not exceed a preset age difference is determined in the week, determining that the relationship between the user and other users in the relationship set of the user is a friendship. For example, assuming that the preset threshold of days is 2 days, the preset age difference is 18, the relationship set of the user a (25 years) includes the users B (50 years), C (48 years) and E (22 years), if the number of days during the week that the night position information of the user a is the same as the night position information of the user B, C is 7 days, and the differences between the age of the user a and the ages of the user B and the user C all exceed the preset age difference 18, the relationship between the user a and the users B, C and E is determined to be a family relationship; for another example, assuming that the preset number-of-days threshold is 2 days, the preset age difference is 18, the relationship set of the user a (25 years) includes the users B (30 years), C (20 years), and E (22 years), and if the number of days during the week in which the nighttime position information of the user a is the same as the nighttime position information of the user B, C is 5 days and the difference between the age of the user a and the age of any user does not exceed the preset age difference 18, it is determined that the relationship between the user a and the users B, C, and E is a friend relationship. By judging the night position data, the relationships between the user and other users in the relationship set of the user can be effectively and accurately identified.
It should be noted that, in this embodiment, user relationship identification of multiple users may be performed, that is, communication data, location data, and the like of batch users are simultaneously acquired, so that user relationship identification is performed on batch users.
According to the embodiment of the invention, the communication data of the user is acquired, the user relationship pair is determined between the user and the associated user of the user according to the communication data, the position data of the user and the position data of the associated user are acquired, the reliable relationship pair is determined in the user relationship pair according to the position data of the user and the position data of the associated user, the relationship set of the user is determined according to the reliable relationship pair, the relationship between the user and other users in the relationship set of the user is determined according to the portrait information of the user and the portrait information of other users in the relationship set of the user, and the interaction behavior of the user and the position data are combined, so that the problems of low coverage rate and low accuracy rate of single data are solved, and the effect of high identification accuracy rate of the user relationship can be achieved.
Fig. 4 is a flowchart illustrating a user relationship identification method according to another embodiment of the present invention. The method may be applied to a computing device. As shown in fig. 4, the method comprises the steps of:
And step 204, determining a reliable relation pair in the user relation pair according to the position data of the user and the position data of the associated user.
Since the user and the associated user may be from different data sources (e.g., different service acceptance systems), a uniform code is required to be used for identification, for example, a Mobile phone number of the user is used as the user identifier, or an International Mobile Equipment Identity (IMEI) of the user is used as the user identifier, and so on.
And step 206, determining a relationship set of the user according to the reliable relationship pair, the user code of the user and the user code of the associated user.
Specifically, as shown in fig. 5, step 206 may include:
step 2063, using the user code of the user and the smaller user code of the first user as the identification of the first reliable relation pair;
step 2064, obtaining a second reliable relation pair in the reliable relation pair, wherein the second reliable relation pair comprises the user and a second user in the associated users;
For example, assume that the reliable relationship pair for user A includes: A-B, A-C, A-E, acquiring a first reliable relation pair A-B, wherein the first reliable relation pair comprises a user A and a first user B, comparing the mobile phone number a of the user A with the mobile phone number B of the user B, and if the mobile phone number a of the user A is smaller, taking the mobile phone number a of the user A as the identification of the first reliable relation pair; if the mobile phone number a of the user A is smaller, the mobile phone number a of the user A is used as the identifier of the second reliable relationship pair; if the mobile phone number E of the user E is smaller, the mobile phone number E of the user E is used as the identifier of the third reliable relationship pair; the identity of the first reliable relationship pair is the same as the identity of the second reliable relationship pair, the first user B and the second user C are taken as a subset of the relationship set of the user a, and the identity of the third reliable relationship pair is different from the identities of the first reliable relationship pair and the second reliable relationship pair, then the third user E cannot be taken as a subset of the relationship set of the user a, i.e. the relationship set of the user a comprises the user a, the user B and the user C.
In this embodiment, if the identifier of the first reliable relationship pair is different from the identifier of the second reliable relationship pair, that is, at least two reliable relationship pairs with the same identifier cannot be obtained in the reliable relationship pair of the user, the user is divided into the relationship sets of other users.
And step 207, determining the weight of the user relationship pair according to the communication data.
Wherein, according to the communication data, determining the weight of the user relationship pair may specifically be: and determining the communication frequency of the user and the associated user according to the communication data, and determining the weight of the user relationship pair according to the communication frequency of the user and the associated user. If the communication frequency of the user and the associated user is high, the weight of the user relation pair is large, and otherwise, if the communication frequency of the user and the associated user is low, the weight of the user relation pair is small.
And step 208, determining the weight of the reliable relationship pair according to the weight of the user relationship pair.
And when the reliable relationship pair is determined in the user relationship pair, acquiring the weight of the user relationship pair at the same time, thereby determining the weight of the reliable relationship pair.
And step 209, determining the relationship set of the user according to the weight of the reliable relationship pair.
Specifically, as shown in fig. 6, step 209 includes:
The other relationship sets refer to relationship sets of other users, and almost every user has its own relationship set in the initial situation. If the user in the relationship set of the user appears in other relationship sets, it is determined that the user in the relationship set of the user appearing in other relationship sets is a duplicate user, for example, it is assumed that the relationship set of the user a includes the user a, the user B, the user C, and the user E, and if the relationship set of the user E includes the user E, the user F, and the user G, it is determined that the user E is a duplicate user.
Wherein the average weight of the reliable relationship pairs is the average of the weights of all reliable relationship pairs in the relationship set. For example, assuming that the relationship set of user a includes user a, user B, user C and user E, the weight of a-B with weight 9,A-C with weight 8,A-E with weight 7, the average weight of reliable relationship pairs in the relationship set of user a is 8, assuming that the relationship set of user E with weight 7,E-G with weight 6, the average weight of reliable relationship pairs in the relationship set of user E is 6.5.
And for the repeated users in the relationship set of the user, if the average weight of the reliable relationship pairs in the relationship set of the user is less than the average weight of other reliable relationship pairs in other relationship sets, removing the repeated users. For example, if it is determined that the user E is a duplicate user, the average weight of reliable relationship pairs in the relationship set of the user a (including the user A, B, C, E) is 8, and the average weight of reliable relationship pairs in the relationship set of the user E (including the user E, F, G) is 6.5, the duplicate user E is removed from the relationship set of the user a.
And step 210, judging whether users which are not divided into any relation set exist in the user relation pair.
Wherein any relationship set comprises the relationship set of the user and other relationship sets of other users except the user. Some relation pairs which do not belong to reliable relation pairs exist in a plurality of user relation pairs of users, and if the relation pairs are not divided into other relation sets in subsequent processing, the users in the relation pairs are users which are not divided into any relation sets.
And step 211, when the user not divided into any relationship set exists in the user relationship pair, adding the user not divided into any relationship set to the relationship set of the user.
For example, assume that the user relationship pair is: A-B, A-C, A-D, A-E, A-F, and determining that user A's relationship set includes user A, B, C, E, if F is not partitioned into any relationship set, adding F to user A's relationship set.
If the user which is not divided into any relationship set and a plurality of users form a user relationship pair at the same time, the user which is not divided into any relationship set is divided into the relationship set with higher average weight in the relationship set.
It should be noted that steps 209, 210, and 211 are repeated until the number of users not classified into the relationship set is lower than the set threshold.
The embodiment of the invention determines a user relationship pair between a user and an associated user of the user according to communication data, acquires position data of the user and position data of the associated user, determines a reliable relationship pair in the user relationship pair according to the position data of the user and the position data of the associated user, acquires a user code of the user and a user code of the associated user, determines a relationship set of the user according to the reliable relationship pair, the user code of the user and the user code of the associated user, arranges the relationship set of the user according to the weight of the reliable relationship pair, determines the relationship between the user and other users in the relationship set according to the portrait information of the user and the portrait information of other users in the relationship set of the user, combines the interaction behavior of the user and the position data, forms the relationship set by the reliable relationship pair, calculates the compactness of the user and the relationship set, solves the problems of low coverage rate and low accuracy rate of single data, can achieve the effect of high identification accuracy rate of the user relationship, and integrated data has unified identification and can be associated with the data in a database, thereby improving the existing degree of the user data.
Fig. 7 illustrates a schematic structural diagram of user relationship identification according to an embodiment of the present invention. As shown in fig. 7, the apparatus 300 includes: a communication data acquisition module 310, a relationship pair determination module 320, a location data acquisition module 330, a reliable relationship pair determination module 340, a relationship set determination module 350, and a relationship type determination module 360.
The communication data obtaining module 310 is configured to obtain communication data of a user; the relationship pair determining module 320 is configured to determine a user relationship pair between the user and an associated user of the user according to the communication data; the location data acquiring module 330 is configured to acquire location data of the user and location data of the associated user; the reliable relationship pair determining module 340 is configured to determine a reliable relationship pair in the user relationship pair according to the location data of the user and the location data of the associated user; the relationship set determining module 350 is configured to determine a relationship set of the user according to the reliable relationship pair; the relationship type determining module 360 is configured to determine relationships between the user and other users in the relationship set of the user according to the portrait information of the user and portrait information of other users in the relationship set of the user.
In an optional manner, the reliable relationship pair determining module 340 is specifically configured to: determining whether a relation user which appears at the same position with the user at the same time exists in the associated users or not according to the position data of the user and the position data of the associated users; and when a relationship user which appears at the same position at the same time as the user exists, determining the user relationship pair of the relationship user as the reliable relationship pair.
In an optional manner, the apparatus 300 further comprises: and an encoding module. And the coding module is used for coding the user and the associated user and acquiring the user code of the user and the user code of the associated user. The relationship set determination module 350 is specifically configured to: obtaining a first reliable relation pair in the reliable relation pair, wherein the first reliable relation pair comprises the user and a first user in the associated users; comparing the user code of the user with the user code of the first user; taking the smaller user code of the user and the user code of the first user as the identifier of the first reliable relationship pair; obtaining a second reliable relation pair in the reliable relation pair, wherein the second reliable relation pair comprises the user and a second user in the associated users; comparing the user code of the user with the user code of the second user; taking the smaller user code of the user and the user code of the second user as the identifier of the second reliable relation pair; and if the identification of the first reliable relation pair is the same as the identification of the second reliable relation pair, taking the first user and the second user as subsets of the relation set of the users.
In an alternative approach, the relationship set determination module 350 includes: the system comprises a first weight determining module, a second weight determining module and a relation set sorting module. The first weight determining module is used for determining the weight of the user relationship pair according to the communication data; the second weight determination module is used for determining the weight of the reliable relationship pair according to the weight of the user relationship pair; and the relationship set sorting module is used for determining the relationship set of the user according to the weight of the reliable relationship pair.
In an optional manner, the relationship set sorting module is specifically configured to: when the user in the relationship set of the user appears in other relationship sets, determining that the user in the relationship set of the user appearing in other relationship sets is a repeated user; calculating the average weight of reliable relation pairs in the relation set of the user and the average weight of other reliable relation pairs in the other relation sets; and if the average weight of the reliable relationship pairs in the relationship set of the user is smaller than the average weight of the other reliable relationship pairs in the other relationship set, removing the repeated user from the relationship set of the user.
In an optional manner, the apparatus 300 further comprises: the device comprises a judgment module and a leakage repairing module. The judging module is used for judging whether users which are not divided into any relation set exist in the user relation pair; and the leakage repairing module is used for adding the users which are not divided into any relation set to the relation set of the user when the users which are not divided into any relation set exist in the user relation pair.
In an optional manner, the relationship type determining module 360 is specifically configured to: acquiring night position information of the user and night position information of other users; and determining the relationship between the user and other users in the relationship set of the user according to the night position information of the user, the night position information of other users, the portrait information of the user and the portrait information of other users.
According to the embodiment of the invention, the communication data of the user is acquired, the user relationship pair is determined between the user and the associated user of the user according to the communication data, the position data of the user and the position data of the associated user are acquired, the reliable relationship pair is determined in the user relationship pair according to the position data of the user and the position data of the associated user, the relationship set of the user is determined according to the reliable relationship pair, the relationship between the user and other users in the relationship set of the user is determined according to the portrait information of the user and the portrait information of other users in the relationship set of the user, and the interaction behavior of the user and the position data are combined, so that the problems of low coverage rate and low accuracy rate of single data are solved, and the effect of high identification accuracy rate of the user relationship can be achieved.
An embodiment of the present invention provides a computer-readable storage medium, where at least one executable instruction is stored in the storage medium, and the executable instruction causes a processor to execute the user relationship identification method in any of the above method embodiments.
According to the embodiment of the invention, the communication data of the user is obtained, the user relationship pair is determined between the user and the associated user of the user according to the communication data, the position data of the user and the position data of the associated user are obtained, the reliable relationship pair is determined in the user relationship pair according to the position data of the user and the position data of the associated user, the relationship set of the user is determined according to the reliable relationship pair, the relationship between the user and other users in the relationship set of the user is determined according to the portrait information of the user and the portrait information of other users in the relationship set of the user, and the interaction behavior of the user is combined with the position data, so that the problems of low coverage rate and low accuracy rate of single data are solved, and the effect of high identification accuracy rate of the user relationship can be achieved.
An embodiment of the present invention provides a computer program product, which includes a computer program stored on a computer storage medium, where the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the user relationship identification method in any of the above-mentioned method embodiments.
According to the embodiment of the invention, the communication data of the user is acquired, the user relationship pair is determined between the user and the associated user of the user according to the communication data, the position data of the user and the position data of the associated user are acquired, the reliable relationship pair is determined in the user relationship pair according to the position data of the user and the position data of the associated user, the relationship set of the user is determined according to the reliable relationship pair, the relationship between the user and other users in the relationship set of the user is determined according to the portrait information of the user and the portrait information of other users in the relationship set of the user, and the interaction behavior of the user and the position data are combined, so that the problems of low coverage rate and low accuracy rate of single data are solved, and the effect of high identification accuracy rate of the user relationship can be achieved.
Fig. 8 is a schematic structural diagram of a computing device according to an embodiment of the present invention, and a specific embodiment of the present invention does not limit a specific implementation of the computing device.
As shown in fig. 8, the computing device may include: a processor (processor) 402, a Communications Interface 404, a memory 406, and a Communications bus 408.
Wherein: the processor 402, communication interface 404, and memory 406 communicate with each other via a communication bus 408. A communication interface 404 for communicating with network elements of other devices, such as clients or other servers. The processor 402 is configured to execute the program 410, and may specifically execute the user relationship identification method in any of the method embodiments described above.
In particular, program 410 may include program code comprising computer operating instructions.
The processor 402 may be a central processing unit CPU, or an Application Specific Integrated Circuit ASIC (Application Specific Integrated Circuit), or one or more Integrated circuits configured to implement an embodiment of the present invention. The computing device includes one or more processors, which may be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
A memory 406 for storing a program 410. Memory 406 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
According to the embodiment of the invention, the communication data of the user is obtained, the user relationship pair is determined between the user and the associated user of the user according to the communication data, the position data of the user and the position data of the associated user are obtained, the reliable relationship pair is determined in the user relationship pair according to the position data of the user and the position data of the associated user, the relationship set of the user is determined according to the reliable relationship pair, the relationship between the user and other users in the relationship set of the user is determined according to the portrait information of the user and the portrait information of other users in the relationship set of the user, and the interaction behavior of the user is combined with the position data, so that the problems of low coverage rate and low accuracy rate of single data are solved, and the effect of high identification accuracy rate of the user relationship can be achieved.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specified otherwise.
Claims (9)
1. A user relationship identification method is characterized by comprising the following steps:
acquiring communication data of a user;
determining a user relationship pair between the user and an associated user of the user according to the communication data;
acquiring the position data of the user and the position data of the associated user;
determining a reliable relation pair in the user relation pair according to the position data of the user and the position data of the associated user;
coding the user and the associated user, and acquiring a user code of the user and a user code of the associated user;
determining a relationship set of the user according to the reliable relationship pair, including: obtaining a first reliable relation pair in the reliable relation pair, wherein the first reliable relation pair comprises the user and a first user in the associated users; comparing the user code of the user with the user code of the first user; taking the smaller user code of the user and the user code of the first user as the identifier of the first reliable relationship pair; obtaining a second reliable relation pair in the reliable relation pair, wherein the second reliable relation pair comprises the user and a second user in the associated users; comparing the user code of the user with the user code of the second user; taking the smaller user code of the user and the user code of the second user as the identifier of the second reliable relation pair; if the identity of the first reliable relationship pair is the same as the identity of the second reliable relationship pair, then the first user and the second user are taken as a subset of the relationship set of the users;
and determining the relationship between the user and other users in the relationship set of the user according to the portrait information of the user and portrait information of other users in the relationship set of the user.
2. The method of claim 1, wherein determining a reliable relationship pair among the user relationship pairs based on the location data of the user and the location data of the associated user, further comprises:
determining whether a relation user which appears at the same position with the user at the same time exists in the associated users or not according to the position data of the user and the position data of the associated users;
and when a relationship user which appears at the same position at the same time as the user exists, determining the user relationship pair of the relationship user as the reliable relationship pair.
3. The method of claim 1, wherein determining the set of relationships for the user from the reliable relationship pair further comprises:
determining the weight of the user relationship pair according to the communication data;
determining the weight of the reliable relationship pair according to the weight of the user relationship pair;
and determining the relationship set of the user according to the weight of the reliable relationship pair.
4. The method of claim 3, wherein determining the set of relationships for the user according to the weights of the reliable relationship pairs further comprises:
when the user in the relationship set of the user appears in other relationship sets, determining that the user appearing in other relationship sets is a repeated user;
calculating the average weight of the reliable relation pairs in the relation set of the user and the average weight of other reliable relation pairs in the other relation sets;
and if the average weight of the reliable relationship pairs in the relationship set of the user is smaller than the average weight of the other reliable relationship pairs in the other relationship set, removing the repeated user from the relationship set of the user.
5. The method of claim 1, further comprising:
when a user which is not divided into any relationship set exists in the user relationship pair, adding the user which is not divided into any relationship set into the relationship set of the user.
6. The method of any one of claims 1-5, wherein determining relationships of the user to other users in the set of relationships of the user based on the representation information of the user and the representation information of other users in the set of relationships of the user, further comprises:
acquiring night position information of the user and night position information of other users;
and determining the relationship between the user and other users in the relationship set of the user according to the night position information of the user, the night position information of other users, the portrait information of the user and the portrait information of other users.
7. An apparatus for identifying user relationships, the apparatus comprising:
the communication data acquisition module is used for acquiring communication data of a user;
a relation pair determining module, configured to determine a user relation pair between the user and an associated user of the user according to the communication data;
a location data acquisition module for acquiring location data of the user and location data of the associated user;
a reliable relationship pair determining module, configured to determine a reliable relationship pair in the user relationship pair according to the location data of the user and the location data of the associated user;
the coding module is used for coding the user and the associated user and acquiring the user code of the user and the user code of the associated user;
a relationship set determining module, configured to determine a relationship set of the user according to the reliable relationship pair, including: obtaining a first reliable relation pair in the reliable relation pair, wherein the first reliable relation pair comprises the user and a first user in the associated users; comparing the user code of the user with the user code of the first user; taking the smaller user code of the user and the user code of the first user as the identifier of the first reliable relationship pair; obtaining a second reliable relation pair in the reliable relation pair, wherein the second reliable relation pair comprises the user and a second user in the associated users; comparing the user code of the user with the user code of the second user; taking the smaller user code of the user and the user code of the second user as the identifier of the second reliable relation pair; if the identity of the first reliable relationship pair is the same as the identity of the second reliable relationship pair, then the first user and the second user are taken as a subset of the relationship set of the users;
and the relationship type determining module is used for determining the relationship between the user and other users in the relationship set of the user according to the portrait information of the user and the portrait information of other users in the relationship set of the user.
8. A computing device, comprising: the system comprises a processor, a memory and a communication interface, wherein the processor, the memory and the communication interface are communicated with each other;
the memory is configured to store at least one executable instruction that causes the processor to perform the operations of the user relationship identification method according to any one of claims 1-6.
9. A computer-readable storage medium having stored therein at least one executable instruction for causing a processor to perform the method of user relationship identification according to any one of claims 1-6.
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