CN113382441A

CN113382441A - Method, device and equipment for identifying companion user and readable storage medium

Info

Publication number: CN113382441A
Application number: CN202110566544.4A
Authority: CN
Inventors: 郭前; 陈涛
Original assignee: China Mobile Communications Group Co Ltd; China Mobile Group Shanxi Co Ltd
Current assignee: China Mobile Communications Group Co Ltd; China Mobile Group Shanxi Co Ltd
Priority date: 2021-05-24
Filing date: 2021-05-24
Publication date: 2021-09-10

Abstract

The application discloses a method, a device, equipment and a readable storage medium for identifying a companion user. Acquiring first time information of a target user and second time information of a first user; next, determining a plurality of groups of time information sets within a plurality of preset time lengths; then, determining user accompanying information of each first user in each group; for each first user, acquiring a first group number corresponding to the condition that the accompanying information of the user is suspected accompanying information and a second group number corresponding to the condition that the accompanying information of the user is not accompanying information; then, determining the time distribution matching success rate and the time distribution matching rate of each first user and the target user; and taking the corresponding first user as the accompanying user of the target user when the time distribution matching success rate and the time distribution matching rate both meet the preset threshold value condition. According to the embodiment of the application, the calculation process can be simplified, and the accuracy of identifying the accompanying user is improved.

Description

Method, device and equipment for identifying companion user and readable storage medium

Technical Field

The present application relates to the field of wireless communications technologies, and in particular, to a method, an apparatus, a device, and a readable storage medium for identifying a companion user.

Background

With the dependence and the use rate of users on mobile phones and the internet becoming higher and higher, operators can accumulate a large amount of real-time position and signaling data of users. Based on the real-time location and the big data of the signaling data, the identification of nearby people and groups of the user location can be performed, i.e. the accompanying users at the user's side are identified.

Currently, there are more and more accompanying calculation technical solutions based on Measurement Report (MR), for example, a fingerprint positioning technology based on a wireless environment calculates a user position first and then determines an accompanying user of the user, which not only has high complexity of a calculation process, but also is affected by wireless signal fluctuation in the wireless environment, and an obtained user position error is large, so that the calculated accompanying user is also inaccurate.

Disclosure of Invention

The embodiment of the application provides a method, a device and equipment for identifying an accompanying user and a readable storage medium, which can simplify the calculation process and improve the accuracy of identifying the accompanying user.

In a first aspect, an embodiment of the present application provides a method for identifying a companion user, where the method includes:

acquiring first time information of a measurement report of target equipment of a target user in a target cell and second time information of the measurement report of first equipment of the first user in the target cell, wherein the target cell comprises a cell where the target equipment is located and adjacent cells of the cell, the first equipment is the first equipment of each first user in the target cell, the number of the first equipment is multiple, the first time information comprises network service connection time of the target equipment, and the second time information comprises network service connection time of the first equipment;

determining a plurality of sets of time information within a plurality of preset time lengths according to the first time information and the plurality of second time information, wherein each set of time information includes: the first time information corresponding to the target equipment in the preset time length and the second time information corresponding to each first equipment in the preset time length;

determining user accompanying information of each first user in each group according to the first time information in each group, the second time information of each first user in each group and a preset similarity algorithm, wherein the user accompanying information comprises suspected accompanying information or non-accompanying information;

for each first user, acquiring a first group number corresponding to the condition that the user accompanying information is suspected accompanying information and a second group number corresponding to the condition that the user accompanying information is non-accompanying information;

determining the time distribution matching success rate and the time distribution matching rate of each first user and the target user according to the first group number and the second group number;

and taking the corresponding first user as the accompanying user of the target user when the time distribution matching success rate and the time distribution matching rate both meet the preset threshold condition.

In some realizations of the first aspect, the determining the user accompanying information of each first user in each group according to the first time information in each group, the second time information of each first user in each group, and a preset similarity algorithm includes:

acquiring a plurality of first received signal strengths of the target device in the target cell and a plurality of second received signal strengths of each first device in the target cell;

and carrying out iterative computation according to the multiple first received signal strengths, the multiple second received signal strengths of each first user and a preset similarity algorithm to obtain the user accompanying information corresponding to each first user.

In some realizations of the first aspect, the obtaining the user accompanying information corresponding to each first user by performing iterative computation according to the multiple first received signal strengths, the multiple second received signal strengths of each first user, and a preset similarity algorithm further includes:

acquiring users corresponding to second time subsection information matched with the first time information in existence time from the first users to obtain second users, and acquiring users corresponding to second time subsection information matched with the first time information in nonexistence time to obtain third users;

calculating a first similarity between a plurality of first received signal strengths of the target user and a plurality of second received signal strengths of the second user according to a preset similarity algorithm;

and determining that the user accompanying information of the corresponding second user is suspected accompanying information when the first similarity is smaller than or equal to a first preset threshold, and determining that the user accompanying information of the corresponding second user is non-accompanying information when the first similarity is larger than the first preset threshold.

In some implementations of the first aspect, the method further comprises:

acquiring users corresponding to second time subsection information of a second user with suspected user accompanying information and having time matching with the second time subsection information of the second user from the third user to obtain a fourth user;

according to a preset similarity algorithm, calculating second similarities of a plurality of second received signal strengths of a second user suspected to accompany the user accompanying information and a plurality of second received signal strengths of a fourth user;

determining that the user accompanying information of the corresponding fourth user is suspected accompanying information when the second similarity is smaller than or equal to a first preset threshold, and determining that the user accompanying information of the corresponding fourth user is non-accompanying information when the second similarity is larger than the first preset threshold;

and continuously carrying out iterative computation according to the first received signal strengths, the second received signal strengths of each first user and a preset similarity algorithm until no additional user accompanying information is a user suspected of being accompanied with information.

In some realizations of the first aspect, the determining a time distribution matching success rate and a time distribution matching rate of each of the first users and the target user according to the first group number and the second group number includes:

in the multiple groups of time information sets, corresponding to each first user, obtaining a third group number corresponding to the condition that the accompanying information of the users is suspected accompanying information and non-accompanying information, and a total group number of the time information sets;

determining the time distribution matching success rate of each first user and the target user according to the ratio of the first group number to the third group number; and the number of the first and second groups,

and determining the time distribution matching rate of each first user and the target user according to the ratio of the third group number to the total group number.

In some implementation manners of the first aspect, the taking, as an accompanying user of the target user, the first user corresponding to the time distribution matching success rate and the time distribution matching rate both meeting a preset threshold condition includes:

and determining that the corresponding first user is a companion user of the target user when the time distribution matching success rate is greater than a second preset threshold and the time distribution matching rate is greater than a third preset threshold.

In a second aspect, an embodiment of the present application provides an apparatus for identifying a companion user, where the apparatus includes:

an obtaining module, configured to obtain first time information of a measurement report of a target device of a target user in a target cell and second time information of a measurement report of a first device of a first user in the target cell, where the target cell includes a cell where the target device is located and a cell adjacent to the cell, the first device is a first device of each first user in the target cell, the number of the first devices is multiple, the first time information includes network service connection time of the target device, and the second time information includes network service connection time of the first device;

a processing module, configured to determine multiple sets of time information sets within multiple preset time lengths according to the first time information and multiple sets of second time information, where each set of time information sets includes: the first time information corresponding to the target equipment in the preset time length and the second time information corresponding to each first equipment in the preset time length;

the calculation module is used for determining the user accompanying information of each first user in each group according to the first time information in each group, the second time information of each first user in each group and a preset similarity algorithm, wherein the user accompanying information comprises suspected accompanying information or non-accompanying information;

the calculation module is further configured to, for each first user, obtain a first group number corresponding to the user accompanying information being suspected accompanying information, and a second group number corresponding to the user accompanying information being non-accompanying information;

the calculation module is further configured to determine a time distribution matching success rate and a time distribution matching rate of each first user and the target user according to the first group number and the second group number;

and the processing module is used for taking the corresponding first user as the accompanying user of the target user when the time distribution matching success rate and the time distribution matching rate both meet the preset threshold value condition.

In some realizations of the second aspect, the calculating module is further configured to obtain a plurality of first reference signal power received signal strengths of the target device in the target cell and a plurality of second reference signal power received signal strengths of each first device in the target cell;

In a third aspect, the present application provides an apparatus for identifying a companion user, the apparatus comprising: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the method of identifying an accompanying user as described in the first aspect or any of the realizable forms of the first aspect.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method of identifying a companion user as set forth in the first aspect or any of the realizable forms of the first aspect.

The embodiment of the application provides a method, a device, equipment and a readable storage medium for identifying an accompanying user, wherein after multiple groups of time information sets of a target cell within multiple preset time lengths are obtained, the accompanying information of a first user, such as suspected accompanying or non-accompanying information, is determined based on time information in each group of time information sets and a preset similarity algorithm, and the time information is grouped according to the preset time lengths, so that the complexity of similarity calculation is effectively reduced, the calculation process is simplified, the accuracy of identifying the accompanying user is improved, whether the first user is the accompanying user of the target user is judged by judging whether the matching success rate and the matching rate of each first user with the target user in each group meet preset threshold conditions or not, and the accuracy of a calculation result is effectively improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a flow chart illustrating a method for identifying a companion user according to an embodiment of the present disclosure;

fig. 2 is a schematic diagram of time information provided in an embodiment of the present application;

fig. 3 is a schematic diagram of grouping time information provided by an embodiment of the present application;

FIG. 4 is a schematic structural diagram of an apparatus for identifying a companion user according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a device for identifying a companion user according to an embodiment of the present application.

Detailed Description

Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative only and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

In order to solve the problem of the prior art, embodiments of the present application provide a method, an apparatus, a device, and a readable storage medium for identifying a companion user. After multiple groups of time information sets of a target cell within multiple first preset time lengths are obtained, the accompanying information of a first user, such as suspected accompanying or non-accompanying, is determined based on the time information in each group of time information sets and a preset similarity algorithm, and the time information is grouped according to the preset time lengths, so that the complexity of similarity calculation is effectively reduced, the calculation process is simplified, errors are avoided, the accuracy of identifying the accompanying users is improved, whether the first user is the accompanying user of the target user is judged by judging whether the matching success rate and the matching rate of each first user between each group of first users and the target user meet preset threshold conditions, and the accuracy of the calculation result is effectively improved.

The following first describes a method for identifying an accompanying user according to an embodiment of the present application.

Fig. 1 is a flowchart illustrating a method for identifying a companion user according to an embodiment of the present application. As shown in fig. 1, the method may include S110 to S160.

S110, obtain first time information of a measurement report of a target device of a target user in a target cell, and second time information of the measurement report of a first device of a first user in the target cell.

The target device may report a measurement report in real time through the wireless communication network, and the measurement report may include, for example, measurement data such as a serving cell where the target device is located or a neighboring cell of the serving cell, signal received power, signal received quality, and the like. For convenience of description, the serving cells are collectively referred to as cells in the present application.

In this embodiment of the present application, the target cell includes a cell where the target device is located and a cell adjacent to the cell, the first device is a first device of each first user in the target cell, the number of the first devices is multiple, the first time information includes network service connection time of the target device, and the second time information includes network service connection time of the first device.

After the target user is determined, the cell where the target user equipment is located and the cell adjacent to the cell, that is, the target cell, can be obtained, and then the first user in the target cell can be determined according to the measurement report corresponding to the target cell.

In some embodiments, the MRO data in the measurement report may include, among other things, raw statistics for each user at each periodic event, and the MRO data may be used for position calculations, positioning calculations, and the like. The MRO data is reported when the user equipment has network service, and the MRO data is not available when the user equipment has no service.

Specifically, the MRO data can be associated with other LTE signaling data such as S1-MME, S1-U and the like, a user number is assigned to the MR data, and the MRO data between the target user and the time range of each first user is extracted through user number filtering.

For convenience of description, a cell in which the target device is located is referred to as a primary serving cell, and a cell adjacent to the primary serving cell is referred to as a neighboring cell.

Illustratively, a data word of MRO data may include: and (3) user identification: MSISDN; time: TIME;

primary serving cell identity and field strength: ECI-SRSRSRP (serving cell field strength);

neighbor 1 identification and field strength: NECI1 (neighbor 1 identity) -NRSRP1 (neighbor 1 field strength);

neighbor cell 2 identification and field strength: NECI2 (neighbor 2 identity) -NRSRP2 (neighbor 2 field strength);

neighbor cell 3 identification and field strength: NECI3 (neighbor 3 identity) -NRSRP3 (neighbor 3 field strength);

neighbor cell 4 identification and field strength: NECI4 (neighbor 4 identity) -NRSRP4 (neighbor 4 field strength);

neighbor 5 identification and field strength: NECI5 (neighbor 5 identity) -NRSRP5 (neighbor 5 field strength);

neighbor cell 6 identification and field strength: NECI6 (neighbor 6 ID) -NRSRP6 (neighbor 6 field intensity)

After the first time information of the target device and the second time information of each first user are acquired, S120 may be performed next.

And S120, determining multiple groups of time information sets within multiple preset time lengths according to the first time information and the multiple second time information.

Wherein each set of time information comprises: the first time information of the target device is corresponded to within the preset time length, and the second time information of each first device is corresponded to within the preset time length.

In some embodiments, when the device of the user is in the service connection state, the MRO data reporting frequency is once every 5 seconds, and taking the target device of the target user as an example, the first time information may include a network service connection time of the target device. The second time information may include a network traffic connection time of the first device. Referring to fig. 2, a may represent a target user and a target device of the target user, B1 to Bn may represent a first user and a first device of the first user, respectively, for example, user a may obtain first time information of user a in a time range from T1 to T2, gray squares represent service connection states at which time user a has network services, and white squares may represent no network services.

As a specific example, as shown in fig. 3, the columns are grouped by time, and the time ranges from T1 to T2 may be divided by preset time lengths, and the group corresponding to each preset time length is determined. Illustratively, the preset time length is 1 minute, and in the time range from T1 to T2, the time length can be divided into m groups. After grouping, each set of time information may be obtained, where each set of time information may include first time information of the user a within a preset time length, and second time information corresponding to the users B1 to Bn within the preset time length, respectively.

Next, S130 may be performed.

And S130, determining the user accompanying information of each first user in each group according to the first time information in each group, the second time information of each first user in each group and a preset similarity algorithm.

The user accompanying information may include suspected accompanying information or non-accompanying information.

In some embodiments, when the first time information of the target user is time-matched with the second time information of the first user, whether the user accompanying information between the target user and the first user is suspected accompanying information or non-accompanying information can be further judged.

Taking packet 1 as an example, as shown in fig. 3, the network traffic connection time of the target device may be included according to the first time information. The second time information may include a network traffic connection time of the first device. It can be obtained that the user a has time matching with the user B1 and the user B2, and then the similarity between the user a and the user B1 and between the user a and the user B2 can be determined according to a preset similarity algorithm, and the user accompanying information of the user B1 and the user B2 can be obtained.

In the embodiment of the application, the time information is grouped according to the preset time length, so that the complexity of similarity calculation is effectively reduced, and the calculation process is simplified.

In some embodiments, in order to accurately determine the accompanying information of each first user, a plurality of first received signal strengths of the target device in the target cell and a plurality of second received signal strengths of each first device in the target cell may be obtained first; and then, carrying out iterative computation according to the multiple first received signal strengths, the multiple second received signal strengths of each first user and a preset similarity algorithm to obtain the user accompanying information corresponding to each first user.

In the target cell, the main serving cell where the target device is located may correspond to a plurality of neighboring cells, and therefore, the received signal strength of the target device in the main serving cell and the received signal strength of the target device in each neighboring cell may be obtained respectively. As a specific example, the received Signal strength may be a Reference Signal Receiving Power (RSRP) obtained from a measurement report.

In order to obtain the user accompanying information corresponding to each first user, specifically, a second user whose time is matched with the first time information of the target user may be determined according to the second time allocation information of all the first users, and then the user accompanying information of each second user is determined, which specifically includes the following steps:

s131, obtaining users corresponding to the second time subsection information matched with the existence time of the first time information from the first users to obtain a second user, and obtaining users corresponding to the second time subsection information matched with the nonexistence time of the first time information to obtain a third user.

It is understood that there is no time match between the first time allocation information of the target user and the second time allocation information of the first user, such as user a and user B3 in group 1 shown in fig. 3.

S132, calculating a first similarity between the first received signal strengths of the target user and the second received signal strengths of the second user according to a preset similarity calculation method.

Taking RSRP as the received signal strength as an example, the plurality of first received signal strengths of the target user may include a first RSRP of the target device in the main serving cell of the target user and a first RSRP of the target device in each neighboring cell.

The plurality of second received signal strengths for the second user may include a second RSRP for each first device at the primary serving cell and a second RSRP for the target device at each neighboring cell.

In some embodiments, the order of the plurality of first RSRP corresponding cells may be different from the order of the plurality of second RSRP corresponding cells, and therefore, the order of the plurality of first RSRP corresponding cells and the order of the plurality of second RSRP corresponding cells may be adjusted to the same order before the first similarity is calculated.

For example, a plurality of first RSRPs corresponding to a user a (target user) may be as shown in table 1, where a represents a primary serving cell, and b, c, and d represent neighboring cells, respectively. A plurality of second RSRPs for user B1 (second user) may be as shown in table 2.

TABLE 1

Cell	RSRP
		Primary serving cell a	S_a
Neighbor b	N_a1
		Neighbor cell c	N_a2
Neighbor cell d	N_a3

TABLE 2

Cell	RSRP
		Primary serving cell a	S_b1
Neighbor cell c	N_b1
		Neighbor b	N_b2
Neighbor cell e	N_b3

As shown in table 1 and table 2, the common cells of the user a and the user B1 include a primary serving cell a, a neighboring cell B, and a neighboring cell c.

In some embodiments, the predetermined similarity algorithm may be, for example, a euclidean algorithm, and the similarity is determined according to the magnitude of the euclidean distance. Specifically, the euclidean distance of user a from user B1 may be as shown in equation (1).

As can be seen from table 1 and table 2, the number of cells shared by user a and user B1 is 3, and therefore, N may take the value of 3.

After the first similarity is obtained, S133 may be performed next.

And S133, determining that the user accompanying information of the corresponding second user is suspected accompanying information when the first similarity is smaller than or equal to a first preset threshold, and determining that the user accompanying information of the corresponding second user is not accompanying information when the first similarity is larger than the first preset threshold.

In the embodiment of the present application, the similarity is expressed by the euclidean distance, and the smaller the euclidean distance, the higher the similarity is, and the larger the euclidean distance, the smaller the similarity is. In the same time and place, the similarity between two sampling points is high under the condition that the difference between the received signal strength of the serving cell and the signal strength of the adjacent cell of the two devices is very small. Therefore, the user accompanying information of the second user corresponding to the first similarity smaller than or equal to the first preset threshold is regarded as suspected accompanying information, and the user accompanying information of the second user corresponding to the first similarity larger than the first preset threshold is regarded as non-accompanying information. The first preset threshold may be set according to actual needs, for example, the value is 5.

After determining the user accompanying information of each of the second users, next, continuing to judge the user accompanying information of each of the third users, and completing the iterative computation, specifically, the method may include the following steps:

s1, the user corresponding to the second time segment information having a time match with the second time segment information of the second user whose accompanying information is suspected to be accompanying is acquired from the third user, and the fourth user is acquired.

S2, according to a preset similarity calculation method, calculates a second similarity between the plurality of second received signal strengths of the second user and the plurality of second received signal strengths of the fourth user, for which the user association information is suspected to be associated.

And S3, determining that the corresponding user accompanying information of the fourth user is suspected accompanying information when the second similarity is smaller than or equal to a first preset threshold, and determining that the corresponding user accompanying information of the fourth user is not accompanying information when the second similarity is larger than the first preset threshold.

And S4, continuing to perform iterative computation according to the multiple first received signal strengths, the multiple second received signal strengths of each first user and a preset similarity algorithm until no additional user accompanying information is a user suspected of being accompanied information.

As a specific embodiment, referring to fig. 3, in which a presence time of a user B1 corresponding to a second user is matched with a presence time of a user a, when a similarity between a user B1 and the user a is smaller than a first preset threshold, the user accompanying information of the user B1 is suspected to be accompanied. Since the user Bn corresponding to the third user does not have a time match with the user a, the user accompanying information of the user Bn does not have a time match before S1 is executed.

User Bn is time matched with user B1 and therefore a second similarity in received signal strength of user Bn and user B1 may be calculated. After the second similarity is obtained, the user accompanying information of the user Bn may be determined next according to S3.

And then, determining whether a user with time matching with the Bn exists from the users with time matching which do not exist in the user accompanying information, if so, continuing to judge the user accompanying information of the user with time matching, and if not, ending the iterative computation.

According to the method for determining the user accompanying information of each first user, provided by the embodiment of the application, the user accompanying information of each first user can be finally obtained. Exemplary, as shown in table 3.

TABLE 3

	Group 1	Group 2	Group 3	……	Packet m
						B1	Suspected of accompanying	Non-concomitant	Suspected of accompanying	Non-concomitant
B2	Suspected of accompanying	Suspected of accompanying	Suspected of accompanying		Suspected of accompanying
						B3	Without time matching	Without time matching	Without time matching	Without time matching
......
						Bn	Non-concomitant	Suspected of accompanying	Non-concomitant	Suspected of accompanying

After determining the user collateral information for each first user in each group, 140 may next be performed.

S140, for each first user, acquiring a first group number corresponding to the condition that the accompanying information of the user is suspected accompanying information and a second group number corresponding to the condition that the accompanying information of the user is not accompanying information.

According to the user accompanying information of each first user in each group, a first group number corresponding to the user accompanying information of the first user when the user accompanying information is suspected accompanying information and a second group number corresponding to the user accompanying information when the user accompanying information is not accompanying information can be determined. Next, S150 may be performed.

S150, determining the time distribution matching success rate and the time distribution matching rate of each first user and the target user according to the first group number and the second group number.

In order to improve the accuracy of identifying the accompanying users, in the embodiment of the present application, the time distribution matching success rate and the time distribution matching rate of each first user and the target user may be respectively determined according to the first group number and the second group number, so as to accurately determine the accompanying users of the target user.

In some embodiments, determining the time distribution matching success rate and the time distribution matching rate of each first user with the target user may include the steps of:

first, in a plurality of sets of time information sets, corresponding to each first user, a third set number corresponding to the case where the accompanying information of the user is suspected accompanying information and non-accompanying information, and a total set number of the time information sets are obtained.

And then, according to the ratio of the first group number to the third group number, determining the time distribution matching success rate of each first user and the target user, and according to the ratio of the third group number to the total group number, determining the time distribution matching rate of each first user and the target user.

And S160, taking the corresponding first user as the accompanying user of the target user when the time distribution matching success rate and the time distribution matching rate both meet the preset threshold value condition.

In some embodiments, the preset threshold condition may include a second preset threshold corresponding to the time distribution matching success rate and a third preset threshold corresponding to the time distribution matching rate.

When the preset threshold condition is determined, taking the corresponding first user as the companion user of the target user may include: and determining that the corresponding first user is a companion user of the target user when the time distribution matching success rate is greater than a second preset threshold and the time distribution matching rate is greater than a third preset threshold.

Illustratively, for example, the second preset threshold is 80%, that is, for the second time information of each first user, at least 80% of all the packets are required to be present and matched with the first time information presence time of the target user. For example, the third preset threshold is 5%, that is, at least 5% of the packets need to exist in the third group number corresponding to the matching existence time, and the user accompanying information of the first user is a suspected accompanying user.

In the embodiment of the application, in order to improve the accuracy of identifying the accompanying users, whether the first user is the accompanying user of the target user is judged by judging whether the matching success rate and the matching rate of each first user between each group of first users and the target user meet the preset threshold conditions, so that the accuracy of the calculation result is effectively improved.

Fig. 4 is a schematic structural diagram of an apparatus for identifying a companion user according to an embodiment of the present application, and as shown in fig. 4, the apparatus 400 for identifying a companion user may include: an acquisition module 410, a processing module 420, and a calculation module 430.

The obtaining module 410 is configured to obtain first time information of a measurement report of a target device of a target user in a target cell, and second time information of a measurement report of a first device of a first user in the target cell, where the target cell includes a cell where the target device is located and a cell adjacent to the cell, the first device is a first device of each first user in the target cell, the number of the first devices is multiple, the first time information includes network service connection time of the target device, and the second time information includes network service connection time of the first device;

a processing module 420, configured to determine, according to the first time information and the plurality of second time information, a plurality of sets of time information within a plurality of preset time lengths, where each set of time information includes: the first time information of the target equipment corresponds to the second time information of each first equipment in the preset time length;

the calculating module 430 is configured to determine user accompanying information of each first user in each group according to the first time information in each group, the second time information of each first user in each group, and a preset similarity algorithm, where the user accompanying information includes suspected accompanying information or non-accompanying information;

the calculating module 430 is further configured to, for each first user, obtain a first group number corresponding to the user accompanying information being suspected accompanying information, and a second group number corresponding to the user accompanying information being non-accompanying information;

the calculating module 430 is further configured to determine a time distribution matching success rate and a time distribution matching rate of each first user and the target user according to the first group number and the second group number;

the processing module 420 is configured to take the corresponding first user as an accompanying user of the target user when both the time distribution matching success rate and the time distribution matching rate meet a preset threshold condition.

In some embodiments, the calculating module 430 is further configured to obtain a plurality of first reference signal power received signal strengths of the target device in the target cell and a plurality of second reference signal power received signal strengths of each first device in the target cell; and performing iterative computation according to the multiple first received signal strengths, the multiple second received signal strengths of each first user and a preset similarity algorithm to acquire user accompanying information corresponding to each first user.

In some embodiments, the user accompanying information further includes non-time matching information, and the calculating module 430 is further configured to obtain, from the first user, a user corresponding to the second time subsection information that is time-matched with the first time information, obtain a second user, and obtain a user corresponding to the second time subsection information that is time-matched with the first time information, not exist, obtain a third user;

the calculating module 430 is further configured to calculate a first similarity between the multiple first received signal strengths of the target user and the multiple second received signal strengths of the second user according to a preset similarity algorithm;

the processing module 420 is further configured to determine that the user accompanying information of the corresponding second user is suspected accompanying information when the first similarity is smaller than or equal to a first preset threshold, and determine that the user accompanying information of the corresponding second user is non-accompanying information when the first similarity is greater than the first preset threshold.

In some embodiments, the calculating module 430 is further configured to obtain, from the third user, a user corresponding to the second time subsection information that is matched with the second time subsection information existing time of the second user whose accompanying information is suspected to be accompanying, so as to obtain a fourth user;

the calculating module 430 is further configured to calculate, according to a preset similarity algorithm, a second similarity between a plurality of second received signal strengths of the second user and a plurality of second received signal strengths of the fourth user, where the user accompanying information is suspected to be accompanying;

the processing module 420 is further configured to determine that the user accompanying information of the corresponding fourth user is suspected accompanying information when the second similarity is smaller than or equal to a first preset threshold, and determine that the user accompanying information of the corresponding fourth user is non-accompanying information when the second similarity is greater than the first preset threshold;

the calculating module 430 is further configured to continue to perform iterative calculation according to the multiple first received signal strengths, the multiple second received signal strengths of each first user, and a preset similarity calculation method until no additional user accompanying information is a user suspected of being accompanied by additional user accompanying information.

In some embodiments, the calculating module 430 is further configured to, in the multiple sets of time information sets, obtain, corresponding to each first user, a third set of numbers corresponding to the cases where the accompanying information of the user is suspected to be accompanying information and non-accompanying information, and a total set of numbers of the time information sets;

the calculating module 430 is further configured to determine a time distribution matching success rate of each first user and the target user according to a ratio of the first group number to the third group number; and determining the time distribution matching rate of each first user and the target user according to the ratio of the third group number to the total group number.

In some embodiments, the processing module 420 is further configured to determine that the corresponding first user is an associated user of the target user when the time distribution matching success rate is greater than a second preset threshold and the time distribution matching rate is greater than a third preset threshold.

It can be understood that the apparatus 400 for identifying an accompanying user in the embodiment of the present application may correspond to an execution subject of the method for identifying an accompanying user provided in the embodiment of the present application, and specific details of operations and/or functions of each module/unit of the apparatus 400 for identifying an accompanying user may refer to the description of the corresponding part in the method for identifying an accompanying user provided in the embodiment of the present application, and for brevity, no further description is provided here.

According to the device for identifying the accompanying users, after multiple groups of time information sets of the target cell within multiple first preset time lengths are obtained, the accompanying information of the first user, such as suspected accompanying or non-accompanying, is determined based on the time information in each group of time information sets and a preset similarity algorithm, and the time information is grouped according to the preset time lengths, so that the complexity of similarity calculation is effectively reduced, the calculation process is simplified, errors are avoided, the accuracy of identifying the accompanying users is improved, whether the first user is the accompanying user of the target user is judged through whether the matching success rate and the matching rate of each first user between each group of first users and the target user meet preset threshold conditions, and therefore the accuracy of calculation results is effectively improved.

Fig. 5 is a schematic structural diagram illustrating a device for identifying a companion user according to an embodiment of the present application. As shown in fig. 5, the apparatus may include a processor 501 and a memory 502 storing computer program instructions.

Specifically, the processor 501 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present Application.

Memory 502 may include a mass storage for information or instructions. By way of example, and not limitation, memory 502 may include a Hard Disk Drive (HDD), a floppy Disk Drive, flash memory, an optical Disk, a magneto-optical Disk, tape, or a Universal Serial Bus (USB) Drive or a combination of two or more of these. In one example, memory 502 can include removable or non-removable (or fixed) media, or memory 502 is non-volatile solid-state memory. The memory 502 may be internal or external to the device that identifies the companion user.

In one example, the Memory 502 may be a Read Only Memory (ROM). In one example, the ROM may be mask programmed ROM, programmable ROM (prom), erasable prom (eprom), electrically erasable prom (eeprom), electrically rewritable ROM (earom), or flash memory, or a combination of two or more of these.

The processor 501 reads and executes the computer program instructions stored in the memory 502 to implement the method described in the embodiment of the present application, and achieves the corresponding technical effect achieved by executing the method in the embodiment of the present application, which is not described herein again for brevity.

In one example, the device that identifies the companion user can also include a communication interface 503 and a bus 510. As shown in fig. 5, the processor 501, the memory 502, and the communication interface 503 are connected via a bus 510 to complete communication therebetween.

The communication interface 503 is mainly used for implementing communication between modules, apparatuses, units and/or devices in the embodiments of the present application.

Bus 510 comprises hardware, software, or both to couple the components of the online information traffic charging apparatus to one another. By way of example, and not limitation, a Bus may include an Accelerated Graphics Port (AGP) or other Graphics Bus, an Enhanced Industry Standard Architecture (EISA) Bus, a Front-Side Bus (Front Side Bus, FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) Bus, an infiniband interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a Micro Channel Architecture (MCA) Bus, a Peripheral Component Interconnect (PCI) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a video electronics standards association local (VLB) Bus, or other suitable Bus or a combination of two or more of these. Bus 510 may include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.

The device for identifying the companion user can execute the recommendation method of the enterprise user service in the embodiment of the application, so that the corresponding technical effect of the method for identifying the companion user described in the embodiment of the application is realized.

In addition, in combination with the method for identifying the companion user in the above embodiments, the embodiments of the present application may be implemented by providing a readable storage medium. The readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any of the above-described embodiments of a method of identifying a companion user.

It is to be understood that the present application is not limited to the particular arrangements and instrumentality described above and shown in the attached drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions or change the order between the steps after comprehending the spirit of the present application.

The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic Circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor Memory devices, Read-Only memories (ROMs), flash memories, Erasable Read-Only memories (EROMs), floppy disks, Compact disk Read-Only memories (CD-ROMs), optical disks, hard disks, optical fiber media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.

It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.

Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware for performing the specified functions or acts, or combinations of special purpose hardware and computer instructions.

As described above, only the specific embodiments of the present application are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application.

Claims

1. A method of identifying a companion user, comprising:

2. The method according to claim 1, wherein the determining the user accompanying information of each first user in each group according to the first time information in each group, the second time information of each first user in each group and a preset similarity algorithm comprises:

3. The method of claim 2, wherein the user profile further includes non-time-matching information, and wherein iteratively calculating according to the first received signal strengths, the second received signal strengths of each first user, and a preset similarity algorithm to obtain the user profile corresponding to each first user comprises:

4. The method of claim 3, further comprising:

5. The method according to claim 1, wherein the determining a time distribution matching success rate and a time distribution matching rate of each of the first users and the target user according to the first group number and the second group number comprises:

6. The method according to claim 1, wherein the taking the corresponding first user as the companion user of the target user when both the time distribution matching success rate and the time distribution matching rate meet a preset threshold condition includes:

7. An apparatus for identifying a companion user, the apparatus comprising:

and the processing module is used for taking the corresponding first user as the accompanying user of the target user when the time distribution matching success rate and the time distribution matching rate both meet the preset threshold condition.

8. The apparatus of claim 7, wherein the computing module is further configured to obtain a plurality of first reference signal power received signal strengths of the target device in the target cell and a plurality of second reference signal power received signal strengths of each first device in the target cell;

9. An apparatus for identifying a companion user, the apparatus comprising: a processor, and a memory storing computer program instructions;

the processor reads and executes the computer program instructions to implement the method of identifying a companion user as claimed in any one of claims 1 to 6.

10. A readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method of identifying a companion user as claimed in any one of claims 1 to 6.