User profiling methods, apparatuses, devices, media, and products

Abstract

The present disclosure provides a user portrait method, device, equipment, medium and product, and relates to the technical field of communication. The method comprises: obtaining attribute information of a user and a plurality of service messages, the service message being a message sent by a terminal used by the user when performing a service, the service message comprising a service identifier representing a service type; counting the service identifiers in the plurality of service messages to obtain a service type statistical result; and performing user portrait according to the service type statistical result and the attribute information of the user. The present disclosure can improve the efficiency of user portrait and the accuracy of user portrait information.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of communication, and in particular, to a user portrait method, a user portrait device, an electronic device, a computer readable storage medium and a computer program product. BACKGROUND

[0002] Generally, when a user is profiled, all the collected business messages need to be comprehensively analyzed to obtain user portrait information.

[0003] However, due to the large amount of data of the business message, the operation amount of the server is increased, the user profiling efficiency is reduced, and the analysis is inaccurate due to the large amount of data, which reduces the accuracy of the user portrait. SUMMARY

[0004] Therefore, the present disclosure provides a user portrait method, a user portrait device, an electronic device, a computer readable storage medium and a computer program product to solve the problem of how to improve the efficiency of user portrait and improve the accuracy of user portrait.

[0005] In a first aspect, the embodiments of the present disclosure provide a user portrait method, which comprises: obtaining attribute information of a user and a plurality of business messages, the business message being a message sent by a terminal used by the user when performing a service, the business message comprising a service identifier representing a service type; counting the service identifiers in the plurality of business messages to obtain a service type statistical result; and performing user portrait according to the service type statistical result and the attribute information of the user.

[0006] In a second aspect, the embodiments of the present disclosure provide a user portrait device, which comprises: an obtaining module configured to obtain attribute information of a user and a plurality of business messages, the business message being a message sent by a terminal used by the user when performing a service, the business message comprising a service identifier representing a service type; a counting module configured to count the service identifiers in the plurality of business messages to obtain a service type statistical result; and a portrait module configured to perform user portrait according to the service type statistical result and the attribute information of the user.

[0007] In a third aspect, the embodiments of the present disclosure provide an electronic device, which comprises: one or more processors; and a memory having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any of the user portrait methods in the embodiments of the present disclosure.

[0008] In a fourth aspect, the embodiments of the present disclosure provide a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, any of the user portrait methods in the embodiments of the present disclosure is implemented.

[0009] In a fifth aspect, the present disclosure provides a computer program product comprising a computer program which, when executed by a processor, implements any of the user portrait methods of the present disclosure.

[0010] The user portrait method in the present disclosure improves the speed of service message statistics by counting the service identifiers in the plurality of service messages without fully analyzing each service message. Further, the user portrait is performed based on the service type statistics result and the attribute information of the user, which can make the obtained user portrait information not only reflect the service attribute, but also reflect the attribute information of the user, thereby improving the accuracy of the user portrait information while improving the efficiency of the user portrait. BRIEF DESCRIPTION OF DRAWINGS

[0011] The accompanying drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of the specification, illustrate embodiments of the present disclosure and serve to explain the principles of the present disclosure, and are not intended to limit the present disclosure. The above and other features and advantages of the present disclosure will become more apparent from the detailed description of the specific embodiments described below, taken in conjunction with the accompanying drawings, in which:

[0012] Figure 1 a flowchart showing a user portrait method provided by an embodiment of the present disclosure;

[0013] Figure 2 a block diagram showing a user portrait device provided by an embodiment of the present disclosure;

[0014] Figure 3 a block diagram showing a user portrait system provided by an embodiment of the present disclosure;

[0015] Figure 4 a flowchart showing another user portrait method provided by an embodiment of the present disclosure;

[0016] Figure 5 a block diagram showing an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] The specific embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely intended to illustrate and explain the present disclosure, and are not intended to limit the present disclosure. The present disclosure can be implemented without some of the specific details by those skilled in the art. The following description of the embodiments is merely intended to provide a better understanding of the present disclosure by showing examples of the present disclosure.

[0018] To make the purpose, technical solutions and advantages of the present disclosure clearer, the specific embodiments of the present disclosure will be described in further detail below with reference to the accompanying drawings.

[0019] With the development of the Internet and big data technology, in order to better analyze the behavior and characteristics of users, a user portrait is usually used to obtain portrait information of different users. When a user is portraited, all the collected business messages need to be comprehensively analyzed to obtain user portrait information.

[0020] However, in order to analyze and process a large amount of business messages, the operation amount of the server needs to be increased, and there is also the problem of inaccurate analysis due to the large amount of data, which not only reduces the efficiency of user portrait, but also cannot guarantee the accuracy of user portrait.

[0021] To solve the above problems, the embodiments of the present disclosure provide a user portrait method, a user portrait device, an electronic device, a computer readable storage medium and a computer program product to improve the efficiency and accuracy of user portrait.

[0022] In a first aspect, the embodiments of the present disclosure provide a user portrait method.

[0023] Figure 1 A flowchart of a user portrait method provided by the embodiments of the present disclosure is shown. The user portrait method can be applied to a user portrait device. As shown in the figure, the user portrait method includes but is not limited to the following steps. Figure 1

[0024] Step S101, obtaining attribute information of a user and a plurality of business messages.

[0025] Among them, the business message is a message sent by a terminal used by the user when performing a service, and the business message includes a service identifier representing a service type.

[0026] The service performed by the user using the terminal can include a plurality of different service types, such as video service, voice service, short message service, etc. Correspondingly, the service identifier matches the service type. That is, when the service performed by the user using the terminal is a voice service, the service identifier in the corresponding business message represents a voice type identifier; when the service performed by the user using the terminal is a video service, the service identifier in the corresponding business message represents a video type identifier; and so on.

[0027] The attribute information of the user includes at least one of the following: a mobile phone number corresponding to the terminal, the age of the user, the user level, the data package information subscribed, the terminal type and the monthly communication cost. The above description of the attribute information of the user is only an example, and can be specifically set according to actual needs. Other unexplained attribute information of the user is also within the protection scope of the present disclosure, and will not be described here.

[0028] ​The user level is a level representing the communication service provided by the operator to the user. For example, the user level is 1, representing that the user is a common user; the user level is 2, representing that the user is an intermediate user, which can be given priority over the user with the user level of 1 when handling the communication service; and so on. Different levels can be set according to actual needs.

[0029] The terminal type is information representing the model and brand of the terminal used by the user, so as to analyze the characteristics of the user using the communication service based on different terminal types.

[0030] In step S102, the service identifiers in the plurality of service messages are counted to obtain a service type counting result.

[0031] When counting the plurality of service messages, only the service identifiers in the service messages need to be counted, without the need of detailed analysis and analysis of each service message, so that the service type counting result can be quickly and accurately obtained.

[0032] For example, when it is determined that there are 5 service identifiers of the voice type, 3 service identifiers of the short message type, and 2 service identifiers of the video type in the 10 service messages, it can be determined that the service type counting result is that the levels of the service types executed by the user from high to low are: voice service, short message service, and video service.

[0033] In step S103, the user portrait is generated based on the service type counting result and the attribute information of the user.

[0034] By combining the service type counting result and the attribute information of the user, the use characteristics of the user when performing the communication service can be comprehensively measured, so that the user can be accurately portraited based on the use characteristics, to obtain the user portrait information reflecting the communication characteristics of the user.

[0035] Further, the operator can provide more accurate communication services for the user according to the obtained user portrait information. For example, if the user portrait information represents that the user tends to use voice services, the corresponding voice package service can be pushed to the user; if the user portrait information represents that the user tends to use data transmission services (such as video download services), the corresponding data flow package service can be pushed to the user to meet the use needs of the user.

[0036] In the embodiment, by counting the service identifiers in the plurality of service messages without the need of comprehensive analysis of each service message, the counting speed of the service messages is improved; further, the user portrait is generated based on the service type counting result and the attribute information of the user, so that the obtained user portrait information can not only reflect the service attribute, but also reflect the attribute information of the user, thereby improving the efficiency of the user portrait and the accuracy of the user portrait information.

[0037] In some example embodiments, the service identifier comprises: a main identifier, or a main identifier and a sub-identifier.

[0038] The main identifier represents a type of the main service, and the sub-identifier represents a type of a sub-service set under the main service. The type of the main service comprises any one of: a video service type, a text service type, a live broadcast service type, and an audio service type.

[0039] Each main service is set with a plurality of sub-services. For example, when the main service is of the live broadcast service type, the corresponding included sub-services are: a shopping live broadcast type, a music live broadcast type, a news live broadcast type, a game live broadcast type, and the like.

[0040] When the main service is of the video service type, the corresponding included sub-services are: a video service type of a movie and television series, a video service type of science popularization, a video service type of news, and the like.

[0041] Therefore, when the service packets executed by the user are counted, the type of the service executed by the user can be preliminarily determined according to the main identifier, and then the specific type of the service executed by the user is further determined according to the sub-identifier, so as to realize accurate positioning of the type of the service executed by the user.

[0042] In some example embodiments, the service type counting result comprises a service discrimination degree corresponding to each service identifier.

[0043] The counting of the service identifiers in the plurality of service packets in step S102 to obtain the service type counting result can be realized in the following manner:

[0044] The number of occurrences of each service identifier in the plurality of service packets is counted; the occurrence frequency of each service identifier is determined according to the number of occurrences corresponding to each service identifier and the total number of all service packets; and the occurrence frequency of each service identifier is smoothed to obtain the service discrimination degree corresponding to each service identifier.

[0045] The number of occurrences corresponding to each service identifier is the number of occurrences of the service identifier in the plurality of service packets collected within a preset time period. For example, if the preset time period is set to 10 minutes, 20 service packets can be collected per minute, and the service identifier to be counted is a voice service identifier, then the number of occurrences of the voice service identifier in the 200 service packets collected within 10 minutes can be counted.

[0046] Since each service packet carries a service identifier, but different service packets carry different service identifiers, the total number of all service packets can also be represented by the total number of all service identifiers appearing in the plurality of service packets.

[0047] For example, if 100 service packets are collected within a preset time length, it can be determined that the total number of all service packets is 100, and the total number of all service identifiers appearing in the 100 service packets collected within the preset time length is also 100.

[0048] The occurrence frequency of each service identifier can be represented as the quotient of the corresponding occurrence number of each service identifier and the total number of all service packets.

[0049] For example, if it is determined by statistics that the occurrence number of a certain service identifier within a preset time length is k, and the total number of all service packets collected within the preset time length is m, then the occurrence frequency f of the service identifier is k / m, where k is a positive integer and m is an integer greater than or equal to k.

[0050] The occurrence frequency of each service identifier is smoothed to obtain the service distinguishability corresponding to each service identifier, so that the statistical data is smoother and the occurrence of extreme values is reduced.

[0051] The smoothing process can be achieved by removing the maximum and minimum values of the occurrence frequency of each service identifier, or by averaging the occurrence frequency of multiple service identifiers. The present disclosure does not limit the way of smoothing the occurrence frequency of each service identifier, as long as it can achieve the smoothing of the occurrence frequency of each service identifier. Therefore, it will not be described here.

[0052] In some exemplary embodiments, the occurrence frequency of each service identifier is smoothed to obtain the service distinguishability corresponding to each service identifier, including: taking the reciprocal of the occurrence frequency of each service identifier, and performing logarithmic operation on the reciprocal of the occurrence frequency to determine the service distinguishability corresponding to the service identifier.

[0053] The service distinguishability corresponding to the service identifier is used to represent the degree to which the target service corresponding to the service identifier is distinguished from other services.

[0054] The service distinguishability p corresponding to the service identifier is calculated using the formula: p = log(1 / f) = log(m / k). Wherein, log() represents logarithmic operation, f represents the occurrence frequency of any service identifier, m represents the total number of all service identifiers appearing in multiple service packets, and k represents the occurrence number of the service identifier in multiple service packets.

[0055] When performing logarithmic operation, the base of the logarithm can be set according to actual needs to adapt to the number of obtained service packets, so that the service distinguishability corresponding to the service identifier obtained finally is more accurate.

[0056] For example, if m is set as 100, k is set as 10, and it is determined to use a base number of 10 for logarithmic operation, then p = log(100 / 10) = lg10 = 1.

[0057] By using the above processing, the smoothing of the statistical result of the service identifier can be achieved, and the occurrence of extreme values can be reduced.

[0058] In some example embodiments, the user portrait is generated according to the service type statistical result and the attribute information of the user, including: marking the terminal used by the user according to the service differentiation degree corresponding to each service identifier, to obtain a service label of the terminal; and generating the user portrait according to the service label of the terminal and the attribute information of the user.

[0059] The service differentiation degree corresponding to each service identifier can determine the type of the service actually performed by the terminal, so that the terminal can be marked to facilitate the use of the service label of the terminal to reflect the type of the most core service performed by the terminal.

[0060] For example, if the terminal used by the user performs multiple different types of services within a preset time period, the service differentiation degrees corresponding to multiple service identifiers can be obtained, and the service differentiation degree corresponding to each service identifier can reflect the degree of differentiation of the target service corresponding to the service identifier from other services. Therefore, by comparing and analyzing the service differentiation degrees corresponding to multiple service identifiers, the service label of the terminal can be determined.

[0061] Further, the user portrait is generated according to the service label of the terminal and the attribute information of the user, which can more accurately reflect the service features performed by the user and the regular attribute features of the user, and the obtained user portrait information is more accurate.

[0062] In some example embodiments, the terminal used by the user is marked according to the service differentiation degree corresponding to each service identifier to obtain a service label of the terminal, including: sorting the service differentiation degrees corresponding to each service identifier to determine a maximum service differentiation degree; and marking the terminal according to the service identifier corresponding to the maximum service differentiation degree to obtain the service label of the terminal.

[0063] The sorting of the service differentiation degrees corresponding to each service identifier can reflect the importance of the target service corresponding to each service identifier relative to other services, and can be arranged in descending order or ascending order. Only the maximum service differentiation degree needs to be obtained, which can represent the service with the most execution times (or the highest execution frequency) within a statistical period.

[0064] Further, according to the service identifier corresponding to the maximum service discrimination degree, the terminal is labeled to determine the service label of the terminal, so that the service label can reflect the characteristics of the service performed by the terminal in the statistical period, facilitating more accurate user profiling in the future.

[0065] In some exemplary embodiments, when the service type includes a shopping type, the method further includes: obtaining payment behavior data corresponding to the terminal; and verifying the user profiling information according to the payment behavior data.

[0066] The payment behavior data corresponding to the terminal is behavior data of the terminal when performing the shopping type service, such as behavior data of the terminal when paying for the purchased items, such as SMS prompts of payment for a certain merchant, and payment success information (such as including payment amount, receiver information, etc.) feedback by a third-party payment platform.

[0067] Through the payment behavior data, the obtained user profiling information can be verified to determine whether the user using the terminal performs the shopping type service in the preset time length (or statistical period) is correct; if the payment behavior data corresponding to the terminal indicates that the user using the terminal has not completed payment after placing an order, it is determined that the user profiling information is inaccurate, and the obtained service message needs to be further analyzed to prompt the accuracy of the user profiling.

[0068] In a second aspect, the embodiments of the present disclosure provide a user profiling device.

[0069] Figure 2 A block diagram showing the composition of a user profiling device provided by the embodiments of the present disclosure is shown. As shown in Figure 2 The user profiling device 200 includes but is not limited to the following modules.

[0070] The acquisition module 201 is configured to acquire attribute information of a user and a plurality of service messages, the service message being a message sent by a terminal used by the user when performing a service, the service message including a service identifier indicating a service type;

[0071] The statistical module 202 is configured to count the service identifiers in the plurality of service messages to obtain a service type statistical result.

[0072] The profiling module 203 is configured to perform user profiling according to the service type statistical result and the attribute information of the user.

[0073] It should be noted that the user profiling device 200 can implement any of the user profiling methods in the present disclosure.

[0074] In the embodiment, the service identifiers in the plurality of service packets are counted by the counting module without full analysis of each service packet, so that the counting speed of the service packets is improved. Further, the user portrait is generated by the portrait module according to the service type counting result and the attribute information of the user, so that the obtained user portrait information can not only reflect the service attribute but also reflect the attribute information of the user, thereby improving the efficiency of the user portrait and the accuracy of the user portrait information.

[0075] It is worth mentioning that each module involved in the embodiment is a logical module. In actual application, one logical unit can be one physical unit, a part of one physical unit, or a combination of multiple physical units. In addition, in order to highlight the innovative part of the disclosure, units not closely related to solving the technical problems proposed in the disclosure are not introduced in the embodiment, but this does not mean that there are no other units in the embodiment.

[0076] In a third aspect, the embodiment of the disclosure provides a user portrait system.

[0077] Figure 3 A constituent block diagram of a user portrait system provided by the embodiment of the disclosure is shown. As shown in Figure 3 The user portrait system includes but is not limited to the following devices: a terminal 301, a base station 302, a portrait server 303, a service server 304, and a service support server 305.

[0078] The terminal 301 and the base station 302 interact with service packets to implement processing of services.

[0079] The service packet includes a service identifier representing a service type.

[0080] In some embodiments, the service identifier is stored in the packet header of each service packet. The service identifier includes a main identifier and a sub-identifier.

[0081] The main identifier represents the type of the main service, and the sub-identifier represents the type of the sub-service set under the main service. The type of the main service includes any one of the following: a video service type, a text service type, a live broadcast service type, and an audio service type.

[0082] For example, if the service identifier includes a main identifier (A1) and a sub-identifier (B1), when the type of the main service represented by A1 is a live broadcast service type, the sub-identifier (B1) can include any one of the following: a shopping live broadcast type, a music live broadcast type, a news live broadcast type, and a game live broadcast type.

[0083] In some embodiments, the main identifier and the sub-identifier can each occupy 2 bytes, for example, the main identifier includes: 00: video service type; 01: text service type; 02: live service type; 03: audio service type;...; and the like. Correspondingly, the sub-service types set under the live service type include: 00: shopping type; 01: music type; 02: news type; 03: game type;...; and the like.

[0084] The main identifier and the sub-identifier are combined and represented as: 0200: shopping live type; 0201: music live type; 0202: news live type; 0203: game live type;...; and the like.

[0085] The portrait server 303 is configured to count the service identifiers in the obtained multiple service messages, obtain a service type counting result, and perform user portrait according to the service type counting result and attribute information of the user.

[0086] The service server 304 is configured to provide the portrait server 303 with service messages, which are messages sent by the terminal 301 to the base station 302 when the terminal 301 performs a service.

[0087] The service support server 305 is configured to provide the portrait server 303 with attribute information of the user using the terminal 301.

[0088] The attribute information of the user includes at least one of the following: a mobile phone number (PhoneNumber) corresponding to the terminal 301, a user priority (User Priority), a subscribed data package information (Plan), a terminal type (Terminal type), and a monthly communication cost (ARPU). The above attribute information of the user is only an example and can be specifically set according to actual needs. Other attribute information of the user not mentioned herein is also within the protection scope of the present disclosure, and will not be described here again.

[0089] Figure 4 A flowchart of another user portrait method provided by an embodiment of the present disclosure is shown. As shown in Figure 4 The user portrait method includes but is not limited to the following steps:

[0090] In step S401, the portrait server 303 sends a first acquisition request to the service support server 305.

[0091] The first acquisition request includes a mobile phone number (for example, 186XXXXXXXX) corresponding to the terminal 301, so as to request the service support server 305 to feed back attribute information of the user corresponding to the mobile phone number to the portrait server 303.

[0092] Step S402, the service support server 305 feeds back a first acquisition response including attribute information of the user to the portrait server 303.

[0093] The first acquisition response includes attribute information of the user, which corresponds to a mobile phone number corresponding to the terminal 301.

[0094] Step S403, the portrait server 303 performs initial portrait of the user according to the acquired attribute information of the user.

[0095] The initial portrait of the user can be embodied in the form of a user tag, which is used to represent the user level and other information of the user.

[0096] Step S404, the portrait server 303 sends a second acquisition request to the service server 304.

[0097] The second acquisition request is used to request to acquire the message header information of the service message sent by the terminal 301 within a preset time length.

[0098] Step S405, the service server 304 feeds back a second acquisition response to the portrait server 303, which carries the message header information of the service message sent by the terminal 301 within the preset time length.

[0099] Step S406, the portrait server 303 performs statistics on the message header information of the service message sent by the terminal 301 within the preset time length, and obtains a service type statistical result.

[0100] The service type statistical result includes a service discrimination degree corresponding to each service identifier.

[0101] In the process of performing statistics on the message header information of the service message sent by the terminal 301 within the preset time length, the following method can be used: counting the number of times of occurrence of the service identifier in each message header information, then determining the occurrence frequency of each service identifier according to the occurrence number corresponding to each service identifier and the total number of all service messages, and performing smoothing processing on the occurrence frequency of each service identifier to obtain the service discrimination degree corresponding to each service identifier.

[0102] Since the service identifiers carried in the message header information of different service messages are different, by counting the number of times of occurrence of the service identifier in each message header information, the specific service type of the service performed by the terminal 301 within the preset time length can be determined.

[0103] For example, when "00" representing the video service type appears once, it is determined that the terminal 301 performs the video service once within the preset time length, and the occurrence number of the video service is increased by 1; when "02" representing the live broadcast service type appears once, it is determined that the terminal 301 performs the live broadcast service once within the preset time length, and the occurrence number of the live broadcast service is increased by 1; when "0200" representing the live shopping type appears once, it is determined that the terminal 301 performs the live shopping service once within the preset time length, and the occurrence number of the live shopping service is increased by 1; and so on.

[0104] Further, for each service identifier, the portrait server 303 calculates the ratio of the occurrence number (k) corresponding to each service identifier and the total number (m) of all service identifiers appearing in the plurality of service messages, and determines the occurrence frequency (f) of each service identifier within the preset time length. Wherein, f=k / m, k is a positive integer, and m is an integer greater than or equal to k.

[0105] Then, the occurrence frequency of each service identifier is taken as an inverse, and the inverse of the occurrence frequency is logarithmically operated to determine the service discrimination degree corresponding to the service identifier.

[0106] For example, the service discrimination degree corresponding to each service identifier is calculated by using the following formula: p=log(1 / f)=log(m / k).

[0107] In some embodiments, if n kinds of service identifiers appear within the preset time length, and the occurrence number of each service identifier is kn, then m=k1+k2+…+kn; n is an integer greater than or equal to 1.

[0108] By calculating the service discrimination degree corresponding to each service identifier, the data can be smoother, the occurrence of extreme values can be reduced, the service discrimination degree corresponding to the service identifier obtained by statistics can be more accurate, and it is beneficial to distinguish different service types according to the service discrimination degree corresponding to the service identifier.

[0109] Further, the service discrimination degree corresponding to the service identifier can reflect the degree of distinguishing the service identifier from other services within the preset time length.

[0110] Step S407, the portrait server 303 sorts the service discrimination degrees corresponding to each service identifier, determines the maximum value of the service discrimination degree, and according to the service identifier corresponding to the maximum value of the service discrimination degree, tags the terminal to obtain the service label of the terminal.

[0111] Wherein, since the service identifier includes a main identifier and a sub-identifier, the service packet can be classified more finely, and the service discrimination maximum value obtained by statistics can represent the type of the main service performed by the terminal in the preset time length, so that the terminal is labeled according to the service identifier corresponding to the service discrimination maximum value, and the type of the service performed by the terminal can be more accurately represented by the obtained service identifier of the terminal, which is beneficial to accurately portrait the user according to the service label of the terminal.

[0112] For example, if it is determined by statistics that the shopping live broadcast type (i.e., the corresponding service identifier is "0200") corresponds to the service discrimination maximum value, it can be determined that the terminal mainly performs the shopping live broadcast service in the preset time length.

[0113] In step S408, the portrait server 303 portraits the user again according to the attribute information of the user and the service label of the terminal, and obtains user portrait information.

[0114] Wherein, the user portrait information obtained by the user portrait can reflect the type of the service performed by the user and the attribute information (such as the level information of the user, the consumption ability, etc.) of the user, which is more convenient for providing different marketing of communication products for the user, so that the user can obtain a communication product that matches the use demand, and the use experience of the user is improved.

[0115] In some examples, the portrait server 303 can also verify the user portrait information according to the subsequent behavior data of the user. For example, in the case where the service type includes a shopping type, the portrait server 303 obtains the payment behavior data corresponding to the terminal; and verifies the user portrait information according to the payment behavior data.

[0116] For example, the portrait server 303 can also interact with the short message service center server (not shown in the figure) to verify whether the user receives the payment behavior data (such as a short message carrying payment amount, etc.), so as to verify the user portrait information.

[0117] If the payment behavior data corresponding to the terminal represents that the terminal has completed the shopping payment, it is determined that the shopping service performed by the user is real, and the user portrait information obtained by the user portrait is also accurate; otherwise, it is determined that the user portrait information is inaccurate, and the user needs to be further portraited.

[0118] In some embodiments, since the attribute information of the user changes dynamically, it is necessary to update the attribute information of the user every certain time length, and the user portrait information is updated regularly, so as to improve the accuracy of the user portrait information, and more accurately recommend the service or communication service required by the user.

[0119] In the embodiment, by counting the service identifiers in the plurality of service packets without fully analyzing each service packet, the speed of counting the service packets is improved, the calculation amount in the user portrait process is greatly reduced, and the data counting efficiency is improved. Further, the user portrait is performed based on the service type counting result and the attribute information of the user, so that the obtained user portrait information can not only reflect the service attribute, but also reflect the attribute information of the user, thereby improving the user portrait efficiency and the accuracy of the user portrait information.

[0120] In a fourth aspect, the embodiments of the present disclosure provide an electronic device, a computer readable storage medium and a computer program product. The above can be used to implement any one of the user portrait methods in the embodiments of the present disclosure, and the corresponding technical solutions and descriptions are referred to the method part and will not be repeated.

[0121] Figure 5 A constituent block diagram of an electronic device provided by the embodiments of the present disclosure is shown.

[0122] As shown in Figure 5 The electronic device includes at least one processor 501, at least one memory 502, and one or more I / O interfaces 503. The processor 501, the memory 502, and the I / O interface 503 are connected to each other through a bus 504. The memory 502 stores one or more computer programs, and the one or more computer programs are executed by the at least one processor 501 to enable the at least one processor 501 to implement any one of the user portrait methods described in the above embodiments.

[0123] The above modules in the electronic device can be all or part realized by software, hardware, and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to the above modules.

[0124] The embodiments of the present disclosure also provide a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor / processing core, implements the above user portrait method. The computer readable storage medium can be a volatile or non-volatile computer readable storage medium.

[0125] The embodiments of the present disclosure also provide a computer program product including computer readable code or a non-volatile computer readable storage medium carrying computer readable code, when the computer readable code is run in the processor of the electronic device, the processor in the electronic device executes the above user portrait method.

[0126] Those of ordinary skill in the art will realize and understand that all or some of the steps in the methods disclosed above and the functional modules / units in the systems and devices can be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementation, the division between the functional modules / units referred to in the above description does not necessarily correspond to the division of physical components; for example, one physical component can have multiple functions, or one function or step can be performed by several physical components in cooperation. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software can be distributed on computer readable storage media, which can include computer storage media (or non-transitory media) and communication media (or transitory media).

[0127] As is well known to those of ordinary skill in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable program instructions, data structures, program modules or other data. Computer storage media include, but are not limited to, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM), static random access memory (SRAM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by a computer. Further, it is well known to those of ordinary skill in the art that communication media typically embodies computer readable program instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. As a result, the foregoing description of computer storage media, along with communication media, applies to and fully integrates software and / or programs such as program modules, program data, and / or computer readable program instructions.

[0128] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0129] Computer readable program instructions for carrying out operations of the present disclosure can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or any combination of one or more of the above in any combination, written in any combination of one or more programming languages, including object oriented programming languages such as Smalltalk, C++ or the like, and conventional procedural programming languages such as "C" or the like. The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0130] The computer program product described herein can be embodied in a specific manner by hardware, software, or a combination thereof. In an optional embodiment, the computer program product is embodied as a computer storage medium. In another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK), and the like.

[0131] The various aspects of the present disclosure are described herein with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer readable program instructions.

[0132] These computer readable program instructions can 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, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can include a non-transitory computer readable storage medium that can be a computer- readable storage medium having no data storage viruses or other code or instructions implementing a functionally equivalent process, such that the instructions, defining functions. The instructions might be stored on the storage device by the manufacturer of the storage device or by later facilities, such as repair shops, storage device

[0133] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0134] The flow diagrams and the block diagrams in the drawings are presented to illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to the present disclosure. In this regard, each block in the flow diagrams and the block diagrams can represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical functions ("instructions"). In some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and

[0135] Example embodiments have been disclosed and, although a specific terminology is employed, it is merely for the convenience of the reader and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, aspects and / or elements described with respect to one embodiment can be used in combination with other embodiments, unless explicitly stated otherwise. Therefore, it is to be understood that various alterations, modifications and / or additions can be made to the examples without departing from the scope of the present disclosure, which is defined by the appended claims.

Claims

1. A user profiling method, characterized by, The method comprises: obtaining attribute information of a user and a plurality of service messages, the service messages being sent by a terminal used by the user when performing a service, the service messages comprising service identifiers representing service types; counting the number of occurrences of each service identifier in the plurality of service messages; determining the occurrence frequency of each service identifier according to the number of occurrences corresponding to each service identifier and the total number of all service messages; and performing smoothing processing on the occurrence frequency of each service identifier to obtain the service discrimination degree corresponding to each service identifier. performing user profiling according to the service type statistical result and the attribute information of the user, the service type statistical result comprising the service discrimination degree corresponding to each service identifier.

2. The method of claim 1, wherein, The service identifier comprises a main identifier, or the main identifier and a sub-identifier. The main identifier represents the type of a main service, and the sub-identifier represents the type of a sub-service set under the main service. The type of the main service comprises any one of the following: a video service type, a text service type, a live broadcast service type, and an audio service type.

3. The method of claim 1, wherein, The smoothing processing on the occurrence frequency of each service identifier to obtain the service discrimination degree corresponding to each service identifier comprises: taking the inverse of the occurrence frequency of each service identifier, and performing logarithmic operation on the inverse of the occurrence frequency to determine the service discrimination degree corresponding to the service identifier. The service discrimination degree corresponding to the service identifier is used to represent the degree to which the target service corresponding to the service identifier is distinguished from other services.

4. The method of claim 1, wherein, The user profiling according to the service type statistical result and the attribute information of the user comprises: labeling the terminal used by the user according to the service discrimination degree corresponding to each service identifier to obtain the service label of the terminal; and performing user profiling according to the service label of the terminal and the attribute information of the user.

5. The method of claim 4, wherein, The labeling of the terminal used by the user according to the service discrimination degree corresponding to each service identifier to obtain the service label of the terminal comprises: sorting the service discrimination degrees corresponding to each service identifier to determine the maximum service discrimination degree; and labeling the terminal according to the service identifier corresponding to the maximum service discrimination degree to obtain the service label of the terminal.

6. The method according to any one of claims 1 to 5, characterized in that, In the case where the service type comprises a shopping type, the method further comprises: obtaining payment behavior data corresponding to the terminal; and verifying the user profiling information according to the payment behavior data.

7. A user profiling apparatus characterized by comprising: The method comprises: an obtaining module configured to obtain attribute information of a user and a plurality of service messages, the service messages being sent by a terminal used by the user when performing a service, the service messages comprising service identifiers representing service types; a counting module configured to count the number of occurrences of each service identifier in the plurality of service messages; determine the occurrence frequency of each service identifier according to the number of occurrences corresponding to each service identifier and the total number of all service messages; perform smoothing processing on the occurrence frequency of each service identifier to obtain the service discrimination degree corresponding to each service identifier; and perform user profiling according to the service type statistical result and the attribute information of the user, the service type statistical result comprising the service discrimination degree corresponding to each service identifier. An image module is configured to generate a user image according to the business type statistical result and attribute information of the user. The business type statistical result includes a business discrimination degree corresponding to each business identifier. 8.An electronic device, comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, and the computer program is executed by the processor to implement the user image method according to any one of claims 1 to 6. 9.A computer readable medium, storing a computer program, wherein the computer program is executed by a processor to implement the user image method according to any one of claims 1 to 6. 10.A computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the user image method according to any one of claims 1 to 6.

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