WO2019085743A1 - 用户性别识别方法、装置、存储介质及电子设备 - Google Patents

用户性别识别方法、装置、存储介质及电子设备 Download PDF

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Publication number
WO2019085743A1
WO2019085743A1 PCT/CN2018/110476 CN2018110476W WO2019085743A1 WO 2019085743 A1 WO2019085743 A1 WO 2019085743A1 CN 2018110476 W CN2018110476 W CN 2018110476W WO 2019085743 A1 WO2019085743 A1 WO 2019085743A1
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user
probability
gender
male
female
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PCT/CN2018/110476
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English (en)
French (fr)
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曾元清
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Oppo广东移动通信有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis

Definitions

  • the present application relates to the field of communications technologies, and in particular, to a user gender identification method, apparatus, storage medium, and electronic device.
  • electronic devices such as mobile phones are becoming more and more popular, and the intelligence of electronic devices is getting higher and higher.
  • electronic devices can automatically provide some services for users, while electronic devices provide some services for users. It is often desirable to know the gender of the user to provide the appropriate service based on the gender of the user.
  • the embodiment of the present application provides a user gender identification method, device, storage medium, and electronic device, which can automatically identify the gender of the user.
  • the user gender identification method provided by the embodiment of the present application includes:
  • the sample of the sample set includes the number of accessing the male application interface for each sample user and the number of female application interfaces accessed by each sample user;
  • the gender of the current user is identified according to the gender probability of the current user.
  • the user gender identification device provided by the embodiment of the present application includes:
  • a establishing unit configured to construct a sample set according to a type of an application interface accessed by the sample user, where the sample of the sample set includes the number of accessing the male application interface of each sample user and the number of accessing the female application interface of each sample user;
  • a training unit configured to train the sample set to generate a gender ratio distribution parameter and an access probability distribution parameter
  • a generating unit configured to generate the gender probability of the current user by using the gender ratio distribution parameter and the access probability distribution parameter, and the number of the current user accessing the male application interface and the number of the current user accessing the female application interface;
  • the identifying unit is configured to identify the gender of the current user according to the gender probability of the current user.
  • a storage medium provided by an embodiment of the present application has a computer program stored thereon, and when the computer program runs on a computer, the computer is configured to perform user gender identification according to the first aspect of the embodiment of the present application. method.
  • an electronic device provided by an embodiment of the present application includes a processor and a memory, where the memory has a computer program, and the processor is configured to perform the method according to the first aspect of the present application by calling the computer program.
  • User gender identification method is configured to perform the method according to the first aspect of the present application by calling the computer program.
  • FIG. 1 is a schematic diagram of an application scenario of a user gender identification method according to an embodiment of the present application.
  • FIG. 2 is a schematic flowchart of a user gender identification method provided by an embodiment of the present application.
  • FIG. 3 is a schematic flowchart diagram of a method for generating various distribution parameters provided by an embodiment of the present application.
  • FIG. 4 is another schematic flowchart of a user gender identification method provided by an embodiment of the present application.
  • FIG. 5 is a schematic structural diagram of a user gender identification apparatus according to an embodiment of the present application.
  • FIG. 6 is another schematic structural diagram of a user gender identification apparatus according to an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • FIG. 8 is another schematic structural diagram of an electronic device according to an embodiment of the present application.
  • the present application implements The example provides a user gender identification method, which can automatically identify the gender of the user.
  • the user gender identification method provided by the embodiment of the present application includes the following steps:
  • the sample of the sample set includes the number of accessing the male application interface for each sample user and the number of female application interfaces accessed by each sample user;
  • the gender of the current user is identified according to the gender probability of the current user.
  • the sample set is trained to generate a gender ratio distribution parameter and an access probability distribution parameter, including:
  • a gender ratio distribution parameter and an access probability distribution parameter are randomly given for the sample set
  • the above two steps are repeatedly performed until the difference between the corresponding parameters obtained twice before and after is less than the preset parameter threshold, and the gender proportional distribution parameter and the access probability distribution parameter are output.
  • the gender of each sample user is generated according to the current gender ratio distribution parameter and the access probability distribution parameter, and the number of male application interfaces accessed by each sample user and the number of female application interfaces accessed by each sample user. Probability, including:
  • the proportion of male users in the sample set the proportion of female users, the probability of male users accessing male application interfaces, the probability of male users accessing female application interfaces, the probability of female users accessing male application interfaces, and females
  • the gender probability of each sample user being a female is determined based on the gender probability of each sample user being a male.
  • the proportion of the male user in the sample set, the proportion of the female user, the probability of the male user accessing the male application interface, the probability of the male user accessing the female application interface, based on the first preset formula The probability of female users accessing the male application interface, the probability of female users accessing the female application interface, and the number of male user application interfaces accessed by each sample user, and the number of female application interfaces accessed by each sample user are processed to generate each
  • the sample user is the gender probability of the male
  • the first preset formula is:
  • j ⁇ [1,n],n represents the number of sample users
  • u j represents the gender probability of the sample user j as a male
  • ⁇ represents the proportion of male users in the sample set
  • 1- ⁇ represents the sample concentration
  • the proportion of female users p (1) indicates the probability of male users accessing the male application interface
  • p (2) indicates the probability of male users accessing the female application interface
  • q (1) indicates the female user accessing the male application interface.
  • Probability, q (2) indicates the probability of a female user accessing a female application interface.
  • 1-u j is determined as the gender probability of the sample user j being a female.
  • the gender ratio distribution parameter and the access probability distribution parameter are generated according to the gender probability of each sample user, including:
  • the probability of a female user accessing the female application interface is generated according to the gender probability of each sample user being a female, the number of female application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user.
  • the gender probability of each sample user is male based on the second preset formula, and the number of sample users is processed to generate a proportion of the male user.
  • the second preset formula is: Determine 1- ⁇ as the proportion of female users;
  • the gender probability of each sample user is male, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user are processed to generate a male user access male application.
  • the probability of the interface, the third preset formula is: Where S represents the total number of application interfaces accessed by each sample user;
  • the gender probability of each sample user being a male, the number of female application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user are processed to generate a male user accessing female application.
  • the probability of the interface, the fourth preset formula is:
  • the female user's access to the male application is generated based on the fifth preset formula, the gender probability of each sample user being a female, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user.
  • the probability of the interface, the fifth preset formula is:
  • the female user's access to the female application is generated based on the sixth preset formula, the gender probability of each sample user being a female, the number of female user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user.
  • the probability of the interface, the sixth preset formula is:
  • the method further includes:
  • the type of the application interface accessed by the sample user is determined according to the set of the male application interface set and the female application interface set.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • Identifying the gender of the current user according to the gender probability of the current user including:
  • the current user is a male gender probability greater than a preset probability threshold, identifying the current user as a male; or
  • the current user is identified as a female.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • Identifying the gender of the current user according to the gender probability of the current user including:
  • the gender probability of the current user being a male is greater than the gender probability of the current user being a female, identifying the current user as a male;
  • the current user is identified as a female.
  • the method further includes:
  • the user gender identification method provided by the embodiment of the present application may be the user gender identification device provided by the embodiment of the present application, or an electronic device integrated with the user gender identification device, wherein the user gender identification device may adopt hardware or software.
  • the electronic device may be a device such as a smart phone, a tablet computer, a palmtop computer, a notebook computer, or a desktop computer.
  • FIG. 1 is a schematic diagram of an application scenario of a user gender identification method according to an embodiment of the present application.
  • the user gender identification device is an electronic device, and the electronic device can obtain related data of an application interface accessed by the sample user from the server.
  • the sample user accesses the image, text, typesetting, sound and other data of the application interface, and the sample user may be a user of unknown gender; according to the acquired data, the type of the application interface accessed by the sample user is determined, according to the application interface accessed by the sample user.
  • the type constructs a sample set, the sample of the sample set includes the number of accessing the male application interface of each sample user and the number of female application interfaces accessed by each sample user; training the sample set to generate a gender proportional distribution parameter And accessing the probability distribution parameter; using the gender ratio distribution parameter and the access probability distribution parameter, and the current number of the user accessing the male application interface and the number of the current user accessing the female application interface, generating the gender probability of the current user,
  • the current user's gender profile Including the current user is the probability of male sex, gender and the current user is the probability of the female; gender probability according to the current user to identify the gender of the current user. For example, the generated current user is male with a gender probability of 0.8, the current user is a female with a gender probability of 0.2, and the current user is male with a higher probability than the current user is female, and the current user is recognized as a male.
  • the embodiment of the present application will describe the user gender identification method provided by the embodiment of the present application from the perspective of the user gender identification device, and the user gender identification device may be specifically integrated in the electronic device.
  • the user gender identification method includes: constructing a sample set according to a type of an application interface accessed by the sample user, the sample of the sample set includes a quantity of each sample user accessing the male application interface and each sample user accessing the female application interface.
  • Quantity training the sample set to generate a gender ratio distribution parameter and an access probability distribution parameter; using the gender ratio distribution parameter and the access probability distribution parameter, and the current number of users accessing the male application interface and the current user accessing the female class Generating the gender probability of the current user by the number of application interfaces; and identifying the gender of the current user according to the gender probability of the current user.
  • a user gender identification method is provided. As shown in FIG. 2, the specific process of the user gender identification method provided in this embodiment may be as follows:
  • Step S201 Construct a sample set according to the type of the application interface accessed by the sample user, where the sample of the sample set includes the number of the male application interface accessed by each sample user and the number of the female application interface accessed by each sample user.
  • an application interface accessed by a male user is masculine, and the application interface accessed by the female user is feminine.
  • masculine game applications such as dungeons, counter-strikes, etc.
  • male-female novels such as military, historical novels
  • male-speaking channels such as sports, car channels.
  • masculine shopping interface such as men's clothing
  • female users usually access the interface of feminine game applications (such as makeup series, dress up series games), feminine novels (such as romance, magic novels) interface, Partial female channels (such as entertainment, gossip channel) interface, feminine shopping interface (such as women's clothing, cosmetics).
  • a male application interface set may include various masculine application interfaces, or include feature information of various masculine application interfaces; the female application interface set may include various biased application interfaces, or include various Characteristic information of the feminine application interface.
  • the type of the application interface accessed by the sample user may be determined according to the set of the male application interface set and the female application interface set. For example, if the application interface accessed by the sample user belongs to the male application interface set, the type of the application interface is determined to be a male application interface; otherwise, if the application interface accessed by the sample user belongs to the female application interface set, the application interface is used. The type is determined to be a female application interface.
  • the type of the application interface is determined to be a male application interface; otherwise, if the feature information of the application interface accessed by the sample user is related to the female If the feature information in the application interface set is matched, the type of the application interface is determined as a female application interface.
  • the electronic device may acquire relevant data of the application interface accessed by the sample user from the server, and then determine the type of the application interface accessed by the sample user according to the set of the male application interface set and the female application interface set.
  • the server may collect relevant data of a preset number of application interfaces that each sample user has continuously accessed in a historical time period according to a preset frequency, and send the collected data to an electronic device that needs to perform user gender recognition. device.
  • the relevant data of the application interface may include but is not limited to: image, text, typesetting, sound and the like of the application interface.
  • the historical time period may be, for example, the past 3 days; the preset frequency may be, for example, every hour; the preset number may be, for example, 1000; the number of sample users may be plural, for example, may be 100.
  • the electronic device determines the number of male application interfaces and female application interfaces among the preset number of application interfaces accessed by each sample user, and builds a sample set according to the determined number.
  • a sample of the sample set includes the number of male application interfaces and the number of female application interfaces in a preset number of application interfaces accessed by a sample user. For example, use x (1) to indicate the number of male application interfaces accessed by a sample user, and x (2) to indicate the number of female application interfaces accessed by a sample user.
  • One sample will include x (1) , x. (2) These two characteristics.
  • the sample set can be as shown in Table 1 below:
  • sample user mentioned in this embodiment may be a user of unknown gender. Therefore, the sample user is not required to actively provide his or her gender, and does not involve user privacy, and each sample has no gender label.
  • Step S202 Train the sample set to generate a gender ratio distribution parameter and an access probability distribution parameter.
  • the gender ratio distribution parameter refers to the proportion of various genders.
  • the gender ratio distribution parameters include: the proportion of male users (represented by ⁇ ) and the proportion of female users (represented by 1- ⁇ ).
  • the access probability distribution parameter refers to the probability that users of various genders access various application interfaces.
  • Access probability distribution parameters include: probability of male users accessing male application interface (represented by p (1) ), probability of male users accessing female application interface ( represented by p (2) ), and female users accessing male application interface Probability (represented by q (1) ), the probability of female users accessing the female application interface ( represented by q (2) ).
  • the two types of parameters can be as shown in Table 2 below:
  • the process of training the sample set to generate a gender ratio distribution parameter and an access probability distribution parameter includes the following steps:
  • Step S2021 Initially, a gender ratio distribution parameter and an access probability distribution parameter are randomly given for the sample set;
  • each parameter represents a ratio or probability
  • each parameter The value range is (0, 1) and satisfies p (1) + p (2) ⁇ a, q (1) + q (2) ⁇ 1-a.
  • the values of given ⁇ , 1- ⁇ , p (1) , p (2) , q (1) , and q (2) are 0.5, 0.5, 0.2, 0.05, 0.06, and 0.3, respectively.
  • Step S2022 Generate a gender probability of each sample user according to the current gender ratio distribution parameter and the access probability distribution parameter, and the number of the male application interface accessed by each sample user and the number of female application interfaces accessed by each sample user.
  • each sample application user interface class women's access to the number of male class application interface, user access to each sample in female
  • the number of application interfaces is used to generate the gender probability of each sample user as a male; according to the gender probability of each sample user as a male, the gender probability of each sample user as a female is determined.
  • the proportion of the male user in the sample set, the ratio of the female user to 1- ⁇ , the probability of the male user accessing the male application interface p (1) , and the male user access may be adopted by using the first preset formula.
  • Women class application interface probability p (2), in men with female users access application interface probability q (1), female users access probability q (2), and each sample application user interface class women's access to male class application interface The quantity, the number of female user application interfaces accessed by each sample user are processed, and the gender probability of each sample user is male, and the first preset formula is:
  • u j represents the gender probability of the sample user j being a male, Indicates the number of sample user j accessing the male application interface. Indicates the number of sample user j accessing the female application interface; 1-u j is determined as the gender probability of the sample user j being a female.
  • Step S2023 Generate a gender ratio distribution parameter and an access probability distribution parameter according to a gender probability of each sample user;
  • the ratio ⁇ of the male user can be generated according to the gender probability u j of each sample user and the number n of sample users.
  • the second preset formula may be used to process the gender probability u j of each sample user and the number n of sample users, to generate a ratio ⁇ of the male user, and the second preset formula is:
  • the proportion of male users is determined.
  • 1- ⁇ can be determined as the proportion of female users.
  • the gender probability u j of each sample user the number of male application interfaces accessed by each sample user And the total number S of application interfaces accessed by each sample user, the probability p (1) of the male user accessing the male application interface is generated.
  • the third preset formula may be used to determine the gender probability u j of each sample user, and the number of male application interfaces accessed by each sample user. And the total number S of application interfaces accessed by each sample user is processed to generate a probability p (1) of the male user accessing the male application interface, and the third preset formula is:
  • the gender probability u j of each sample user the number of female application interfaces accessed by each sample user And the total number S of application interfaces accessed by each sample user, the probability p (2) of the male user accessing the female application interface is generated.
  • the fourth preset formula may be used to determine the gender probability u j of each sample user and the number of female application interfaces accessed by each sample user. And the total number S of application interfaces accessed by each sample user is processed to generate a probability p (2) of the male user accessing the female application interface, and the fourth preset formula is:
  • the gender probability 1-u j of each sample user the number of male application interfaces per sample user access And the total number S of application interfaces accessed by each sample user, the probability q (1) of the female user accessing the male application interface is generated.
  • the fifth preset formula can be used to determine the gender probability 1-u j of each sample user as a female, and the number of male application interfaces accessed by each sample user. And the total number S of application interfaces accessed by each sample user is processed to generate a probability q (1) of the female user accessing the male application interface, and the fifth preset formula is:
  • the gender probability 1-u j of each sample user the number of female application interfaces accessed by each sample user And the total number S of application interfaces accessed by each sample user, the probability q (2) of the female user's access to the female application interface is generated.
  • the sixth preset formula can be used to determine the gender probability 1-u j of each sample user, and the number of female application interfaces accessed by each sample user. And the total number S of application interfaces accessed by each sample user is processed to generate a probability q (2) of the female user accessing the female application interface, and the sixth preset formula is:
  • Step S2024 determining whether the difference between the corresponding parameters obtained twice before and after is less than the preset parameter threshold, and if so, executing step S2025, otherwise, returning to step S2022;
  • the preset parameter threshold can be customized according to actual needs. For example, it can take 0.001.
  • the absolute value of the difference between the corresponding parameters obtained twice before and after may be calculated. If the absolute value of the difference of the corresponding parameter is not less than the preset parameter threshold, the process returns to step S2022 to continue. Iterating until the absolute value of the difference of the corresponding parameters is less than the preset parameter threshold, the iteration is stopped.
  • Step S2025 outputting a gender ratio distribution parameter and an access probability distribution parameter.
  • FIG. 3 shows a process for obtaining each probability distribution parameter by using an Expectation Maximization Algorithm (EM), where step S2022 is the E step of the EM algorithm, and step S2023 is the M step of the EM algorithm.
  • EM Expectation Maximization Algorithm
  • step S2021 to step S2025 may be completed in advance in the server.
  • the server may train the sample set to obtain each probability distribution parameter, and send the obtained probability distribution parameter to the electronic device that needs to perform gender recognition, and the electronic device identifies the gender of a certain user according to each obtained probability distribution parameter.
  • Step S203 Generate the gender probability of the current user by using the gender ratio distribution parameter and the access probability distribution parameter, and the number of the current user accessing the male application interface and the number of the current user accessing the female application interface.
  • the current user is i
  • the current user is the user of the current electronic device
  • the preset number of application interfaces that the current user has recently accessed may be collected, and the number of male application interfaces in the preset number of application interfaces is counted.
  • the number of female application interfaces The seventh preset formula is used to generate a gender probability u i of the current user as a male, and the seventh preset formula is:
  • the gender probability of the current user being a female is 1-u i .
  • Step S204 Identify the gender of the current user according to the gender probability of the current user.
  • the size of u i and 1-u i can be determined. If u i is greater than 1-u i , the current user is recognized as a male; conversely, if u i is less than 1-u i , the current user is recognized as a female.
  • the current user After identifying the current user's gender, you can do some information or application push for the current user based on gender. For example, when it is recognized that the current user is a male, the current user may be pushed to play some new games suitable for males. When the current user is identified as a female, the current user may be given some cosmetic promotion information, etc., of course, Some other optimizations are made based on the identified gender, which is not specifically limited here.
  • the sample set can be constructed according to the number of application interfaces of each type accessed by the sample user, and the sample set is trained to generate the gender ratio distribution parameter and the access probability distribution parameter, and the generated gender ratio distribution parameter and the access probability distribution are utilized.
  • the parameter identifies the gender of the current user and realizes the automatic identification of the user's gender.
  • another user gender identification method is provided. As shown in FIG. 4, this embodiment will construct a sample set by collecting 1000 application interfaces recently accessed by 100 sample users to identify the current current electronic device. The gender of the user is taken as an example for description. The method of this embodiment includes:
  • Step S401 setting a male application interface set and a female application interface set.
  • the gender of the user includes: male and female.
  • two types of application interface sets may be set: a male application interface set and a female application interface set.
  • the male application interface set may include various masculine application interfaces, or include feature information of various masculine application interfaces; the female application interface set may include various biased application interfaces, or include various Characteristic information of the feminine application interface.
  • Step S402 Determine, according to the set of the male application interface set and the female application interface set, the type of the application interface accessed by the sample user.
  • the type of the application interface is determined to be a male application interface; otherwise, if the application interface accessed by the sample user belongs to the female application interface set, the application interface is used. The type is determined to be a female application interface.
  • the type of the application interface is determined to be a male application interface; otherwise, if the feature information of the application interface accessed by the sample user is related to the female If the feature information in the application interface set is matched, the type of the application interface is determined as a female application interface.
  • the electronic device may acquire relevant data of the application interface accessed by the sample user from the server, and then determine the type of the application interface accessed by the sample user according to the set of the male application interface set and the female application interface set.
  • the server may collect data related to 1000 application interfaces that are continuously accessed by 100 sample users from 100 electronic devices in a historical time period according to a preset frequency, and send the collected data to an electronic device that needs to perform user gender recognition.
  • the relevant data of the application interface may include but is not limited to: image, text, typesetting, sound and the like of the application interface.
  • the historical time period can be, for example, the last 3 days; the preset frequency can be, for example, every hour.
  • Step S403 Construct a sample set according to the type of the application interface accessed by the sample user, where the sample of the sample set includes the number of the male application interface accessed by each sample user and the number of the female application interface accessed by each sample user.
  • the electronic device determines the number of male application interfaces and female application interfaces among the 1000 application interfaces that each sample user has recently accessed in a row, and builds a sample set according to the determined number.
  • the sample set consists of 100 samples, one sample, including the number of male application interfaces and the number of female application interfaces among the 1000 application interfaces that a sample user has recently accessed. For example, use x (1) to indicate the number of male application interfaces accessed by a sample user, and x (2) to indicate the number of female application interfaces accessed by a sample user.
  • One sample will include x (1) , x. (2) These two characteristics.
  • a sample set of 100 samples can be expressed as:
  • the 100 sample users mentioned in this embodiment may be users of unknown gender. Therefore, the sample users are not required to actively provide their own gender, and no user privacy is involved, and each sample has no gender label.
  • Step S404 training the sample set to generate a gender ratio distribution parameter and an access probability distribution parameter.
  • the gender ratio distribution parameter refers to the proportion of various genders.
  • the gender ratio distribution parameters include: the proportion of male users (represented by ⁇ ) and the proportion of female users (represented by 1- ⁇ ).
  • the access probability distribution parameter refers to the probability that users of various genders access various application interfaces.
  • Access probability distribution parameters include: probability of male users accessing male application interface (represented by p (1) ), probability of male users accessing female application interface ( represented by p (2) ), and female users accessing male application interface Probability (represented by q (1) ), the probability of female users accessing the female application interface ( represented by q (2) ).
  • the purpose of the training is to obtain ⁇ , 1- ⁇ , p (1) , p (2) , q (1) , q (2) .
  • the specific training process refer to the description of the above embodiment, and no further description is provided here. .
  • Step S405 Generate the gender probability of the current user by using the gender ratio distribution parameter and the access probability distribution parameter, and the number of the current user accessing the male application interface and the number of the current user accessing the female application interface.
  • the seventh preset formula is used to generate a gender probability u i of the current user as a male, and the seventh preset formula is:
  • the gender probability of the current user being a female is 1-u i .
  • step S406 it is determined whether the gender probability of the current user is greater than the preset probability threshold. If yes, step S407 is performed; otherwise, step S408 is performed.
  • Step S407 identifying the current user as a male.
  • Step S408 Determine whether the gender probability of the current user is a female is greater than a preset probability threshold. If yes, execute step S409, otherwise end the process.
  • Step S409 identifying the current user as a male.
  • the preset probability threshold can be customized according to actual needs, for example, 0.8, 0.85, etc. can be taken.
  • u i or 1-u i is greater than a preset probability threshold. If u i is greater than a preset probability threshold, the current user is identified as a male, and if 1-u i is greater than a preset probability threshold, the current user is identified. For women.
  • the gender of the current user can also be identified directly by judging the size of u i and 1-u i . For example, if u i is greater than 1-u i , the current user is recognized as a male, and if u i is less than 1-u i , the current user is recognized as a female.
  • the method of comparing the sizes of u i and 1-u i may also be used to identify the gender of the current user. Or, when both u i and 1-u i are not greater than the preset probability threshold, re-acquiring the sample data to reconstruct the sample set to update each probability distribution parameter, and then recalculating the current user's gender probability; or in u i and 1 When -u i is not greater than the preset probability threshold, the current user's application interface access data is re-acquired to recalculate the current user's gender probability.
  • the current user After identifying the current user's gender, you can do some information or application push for the current user based on gender. For example, when the current user is identified as a male, some current live broadcast information may be pushed to the current user. When the current user is identified as a female, the current user may be prompted to push some entertainment dynamic information, etc., of course,
  • the gender does some other optimizations and is not specifically limited here.
  • the sample set can be constructed according to the number of application interfaces of each type accessed by the sample user, and the sample set is trained to generate the gender ratio distribution parameter and the access probability distribution parameter, and the generated gender ratio distribution parameter and the access probability distribution are utilized.
  • the parameter identifies the gender of the current user and realizes the automatic identification of the user's gender.
  • the embodiment of the present application further provides a user gender identification device, including an establishing unit, a training unit, a generating unit, and an identifying unit, as follows:
  • a establishing unit configured to construct a sample set according to a type of an application interface accessed by the sample user, where the sample of the sample set includes the number of accessing the male application interface of each sample user and the number of accessing the female application interface of each sample user;
  • a training unit configured to train the sample set to generate a gender ratio distribution parameter and an access probability distribution parameter
  • a generating unit configured to generate the gender probability of the current user by using the gender ratio distribution parameter and the access probability distribution parameter, and the number of the current user accessing the male application interface and the number of the current user accessing the female application interface;
  • the identifying unit is configured to identify the gender of the current user according to the gender probability of the current user.
  • the training unit comprises:
  • Initializing a subunit configured to randomly give a gender ratio distribution parameter and an access probability distribution parameter for the sample set at an initial time
  • the generating subunit generates each of the current gender ratio distribution parameters and the access probability distribution parameters, and the number of each of the sample users accessing the male application interface and the number of female application interfaces accessed by each sample user.
  • Gender probability of sample users including:
  • the generating subunit is based on a proportion of male users in the sample set, a proportion of female users, a probability of male users accessing a male application interface, a probability of a male user accessing a female application interface, and a female user accessing a male application.
  • the generating sub-unit determines a gender probability that each sample user is a female according to a gender probability of each sample user being a male.
  • the generating subunit generates a gender ratio distribution parameter and an access probability distribution parameter according to a gender probability of each sample user, including:
  • the generating subunit generates a proportion of the male user according to the gender probability of each sample user being a male and the number of sample users;
  • the generating subunit determines the proportion of the female user according to the proportion of the male user
  • the generating subunit generates a probability that the male user accesses the male application interface according to the gender probability of each sample user being a male, the number of male application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user. ;
  • the generating subunit generates a probability that the male user accesses the female application interface according to the gender probability of each sample user being a male, the number of female application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user. ;
  • the generating sub-unit generates a probability that the female user accesses the male application interface according to the gender probability of each sample user being a female, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user. ;
  • the generating sub-unit generates a probability that the female user accesses the female application interface according to the gender probability of each sample user being a female, the number of female user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user. .
  • the apparatus further includes:
  • a setting unit for setting a male application interface set and a female application interface set
  • the determining unit is configured to determine, according to the set male application interface set and the female application interface set, the type of the application interface accessed by the sample user.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • the identification unit is specifically configured to:
  • the current user When the gender probability that the current user is a male is greater than a preset probability threshold, the current user is identified as a male; or when the gender probability that the current user is a female is greater than the preset probability threshold, the current The user is identified as a female.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • the identification unit is specifically configured to:
  • the current user When the current user is a male gender probability greater than the current user is a female gender probability, the current user is identified as a male; or the current user is a female gender probability greater than the current user is a male The current user is identified as a female when the gender probability.
  • the apparatus further includes:
  • a pushing unit configured to push information or an application for the current user according to the gender recognition result of the current user.
  • a user gender identification device is further provided, and the user gender identification device is applied to an electronic device.
  • the user gender identification device includes: an establishing unit 501, a training unit 502, and a generating unit 503. And identification unit 504, as follows:
  • the establishing unit 501 is configured to construct a sample set according to the type of the application interface accessed by the sample user, where the sample of the sample set includes the number of accessing the male application interface of each sample user and the number of female application interfaces accessed by each sample user. ;
  • the training unit 502 is configured to train the sample set to generate a gender ratio distribution parameter and an access probability distribution parameter;
  • a generating unit 503 configured to generate the gender probability of the current user by using the gender ratio distribution parameter and the access probability distribution parameter, and the number of the current user accessing the male application interface and the number of the current user accessing the female application interface;
  • the identifying unit 504 is configured to identify the gender of the current user according to the gender probability of the current user.
  • the training unit 502 includes an initialization subunit 5021 and a generation subunit 5022, as follows:
  • An initialization subunit 5021 configured to randomly give a gender ratio distribution parameter and an access probability distribution parameter for the sample set at an initial time
  • the generating sub-unit 5022 is configured to generate each sample user according to the current gender ratio distribution parameter and the access probability distribution parameter, and the number of male application interfaces accessed by each sample user and the number of female application interfaces accessed by each sample user. a gender probability; generating a gender ratio distribution parameter and an access probability distribution parameter according to the gender probability of each sample user; the generation subunit 5022 repeatedly performs the above two steps until the difference between the corresponding parameters obtained twice before and after is less than When the parameter threshold is set, the gender ratio distribution parameter and the access probability distribution parameter are output.
  • the generating sub-unit 5022 is based on the current gender ratio distribution parameter and the access probability distribution parameter, and the number of male user application interfaces accessed by each sample user and the number of female application interfaces accessed by each sample user. Generate gender probabilities for each sample user, including:
  • the generating subunit 5022 is based on the proportion of male users in the sample set, the proportion of female users, the probability of male users accessing male application interfaces, the probability of male users accessing female application interfaces, and female users visiting males. Probability of the application interface, the probability of female users accessing the female application interface, and the number of male application interfaces accessed by each sample user, the number of female application interfaces accessed by each sample user, and the gender probability of each sample user being male ;and
  • the generating sub-unit 5022 determines the gender probability that each sample user is a female according to the gender probability of each sample user being a male.
  • the generating subunit 5022 is based on a ratio of a male user in the sample set, a proportion of a female user, a probability of a male user accessing a male application interface, and a male user access based on a first preset formula.
  • the probability of female application interface, the probability of female users accessing male application interface, the probability of female users accessing female application interface, and the number of male user application interfaces accessed by each sample user, and each sample user accessing female application interface The quantity is processed to generate a gender probability that each sample user is a male, and the first preset formula is:
  • j ⁇ [1,n],n represents the number of sample users
  • u j represents the gender probability of the sample user j as a male
  • ⁇ represents the proportion of male users in the sample set
  • 1- ⁇ represents the sample concentration
  • p (1) indicates the probability of male users accessing the male application interface
  • p (2) indicates the probability of male users accessing the female application interface
  • q (1) indicates the female user accessing the male application interface.
  • Probability, q (2) indicates the probability of a female user accessing a female application interface.
  • the generating subunit 5022 determines the 1-u j j is a sample user Gender Female probability.
  • the generating sub-unit 5022 generates a gender ratio distribution parameter and an access probability distribution parameter according to the gender probability of each sample user, including:
  • the generating sub-unit 5022 generates a proportion of the male user according to the gender probability of each sample user being a male and the number of sample users;
  • the generating subunit 5022 determines the proportion of the female user according to the proportion of the male user
  • the generating sub-unit 5022 generates a male user accessing the male application interface according to the gender probability of each sample user being a male, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user. Probability
  • the generating sub-unit 5022 generates a male user accessing the female application interface according to the gender probability of each sample user being a male, the number of female user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user. Probability
  • the generating sub-unit 5022 generates a female user visiting the male in the sample set according to the gender probability that each sample user is a female, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user.
  • the generating sub-unit 5022 generates a female user accessing the female application interface according to the gender probability of each sample user being a female, the number of female user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user. Probability.
  • the generating sub-unit 5022 processes the gender probability of each sample user as a male, and the number of sample users according to a second preset formula, to generate a proportion of the male user, the second pre- Let the formula be:
  • the generating subunit 5022 determines 1- ⁇ as the proportion of the female user
  • the generating sub-unit 5022 processes the gender probability of each sample user as a male, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user based on a third preset formula, and generates The probability that a male user accesses a male application interface, and the third preset formula is: Where S represents the total number of application interfaces accessed by each sample user;
  • the generating sub-unit 5022 processes, according to the fourth preset formula, the gender probability of each sample user as a male, the number of female user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user, and generates The probability that a male user accesses a female application interface, and the fourth preset formula is:
  • the generating sub-unit 5022 processes, according to a fifth preset formula, a gender probability that each sample user is a female, a number of male user application interfaces accessed by each sample user, and a total number of application interfaces accessed by each sample user, and generates The probability that a female user accesses a male application interface, and the fifth preset formula is:
  • the generating sub-unit 5022 processes, according to a sixth preset formula, a gender probability that each sample user is a female, a number of female user application interfaces accessed by each sample user, and a total number of application interfaces accessed by each sample user, and generates The probability that a female user accesses a female application interface, and the sixth preset formula is:
  • the apparatus further includes a setting unit 505 and a determining unit 506, as follows:
  • the setting unit 505 is configured to set a male application interface set and a female application interface set;
  • the determining unit 506 is configured to determine, according to the set of the male application interface set and the female application interface set, the type of the application interface accessed by the sample user.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • the identification unit 504 is specifically configured to:
  • the current user When the gender probability that the current user is a male is greater than a preset probability threshold, the current user is identified as a male; or when the gender probability that the current user is a female is greater than the preset probability threshold, the current The user is identified as a female.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • the identification unit 504 is specifically configured to:
  • the current user When the current user is a male gender probability greater than the current user is a female gender probability, the current user is identified as a male; or the current user is a female gender probability greater than the current user is a male The current user is identified as a female when the gender probability.
  • the apparatus further includes:
  • the pushing unit 507 is configured to push information or an application for the current user according to the gender recognition result of the current user.
  • the user gender identification device provided by the embodiment is only illustrated by the division of the above functional modules. In an actual application, the functions may be allocated by different functional modules as needed. Upon completion, the internal structure of the device is divided into different functional modules to perform all or part of the functions described above.
  • the user gender identification device and the user gender identification method provided by the above embodiments are in the same concept, and the specific implementation process is described in detail in the method embodiment, and details are not described herein again.
  • the setting unit 501 constructs a sample set according to the number of various types of application interfaces accessed by the sample user, and the training unit 502 generates a gender ratio distribution parameter and an access probability by training the sample set.
  • the distribution parameter, the generating unit 503 generates the gender probability of the current user by using the gender ratio distribution parameter and the access probability distribution parameter, and the number of the current user accessing the male application interface and the number of the current user accessing the female application interface.
  • the unit 504 identifies the gender of the current user according to the gender probability of the current user, and realizes automatic identification of the user gender; and obtains various distribution parameters by training the sample set, and then performs a user gender recognition method to ensure the recognition result.
  • the accuracy provides an effective reference for gender-based services.
  • the electronic device 600 includes a processor 601 and a memory 602.
  • the processor 601 is electrically connected to the memory 602.
  • the processor 600 is a control center of the electronic device 600 that connects various portions of the entire electronic device using various interfaces and lines, by running or loading a computer program stored in the memory 602, and recalling data stored in the memory 602, The various functions of the electronic device 600 are performed and data is processed to thereby perform overall monitoring of the electronic device 600.
  • the memory 602 can be used to store software programs and modules, and the processor 601 executes various functional applications and data processing by running computer programs and modules stored in the memory 602.
  • the memory 602 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, a computer program required for at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may be stored according to Data created by the use of electronic devices, etc.
  • memory 602 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, memory 602 can also include a memory controller to provide processor 601 access to memory 602.
  • the processor 601 in the electronic device 600 loads the instructions corresponding to the process of one or more computer programs into the memory 602 according to the following steps, and is stored in the memory 602 by the processor 601.
  • the computer program in which to implement various functions, as follows:
  • the sample of the sample set includes the number of accessing the male application interface for each sample user and the number of female application interfaces accessed by each sample user;
  • the gender of the current user is identified according to the gender probability of the current user.
  • the processor 601 when the sample set is trained to generate a gender ratio distribution parameter and an access probability distribution parameter, the processor 601 specifically performs the following steps:
  • a gender ratio distribution parameter and an access probability distribution parameter are randomly given for the sample set
  • the above two steps are repeatedly performed until the difference between the corresponding parameters obtained twice before and after is less than the preset parameter threshold, and the gender proportional distribution parameter and the access probability distribution parameter are output.
  • each sample user is generated based on current gender proportional distribution parameters and access probability distribution parameters, and the number of male user application interfaces accessed by each sample user and the number of female application interfaces accessed by each sample user.
  • the processor 601 performs the following steps:
  • the proportion of male users in the sample set the proportion of female users, the probability of male users accessing male application interfaces, the probability of male users accessing female application interfaces, the probability of female users accessing male application interfaces, and females
  • the gender probability of each sample user being a female is determined based on the gender probability of each sample user being a male.
  • the processor 601 is specifically configured to use a proportion of a male user in the sample set based on a first preset formula, a proportion of a female user, a probability of a male user accessing a male application interface, and a male user.
  • the probability of accessing the female application interface, the probability of female users accessing the male application interface, the probability of female users accessing the female application interface, and the number of male application interfaces accessed by each sample user, and each sample user accessing the female application interface The quantity is processed to generate a gender probability that each sample user is a male, and the first preset formula is:
  • j ⁇ [1,n],n represents the number of sample users
  • u j represents the gender probability of the sample user j as a male
  • ⁇ represents the proportion of male users in the sample set
  • 1- ⁇ represents the sample concentration
  • p (1) indicates the probability of male users accessing the male application interface
  • p (2) indicates the probability of male users accessing the female application interface
  • q (1) indicates the female user accessing the male application interface.
  • Probability, q (2) indicates the probability of a female user accessing a female application interface.
  • Processor 601 1-u j j is determined to be a sample user Gender probability of women.
  • the processor 601 when generating the gender ratio distribution parameter and the access probability distribution parameter according to the gender probability of each sample user, the processor 601 is specifically configured to perform the following steps:
  • the probability of the female user accessing the female application interface in the sample set is generated according to the gender probability of each sample user being a female, the number of female application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user.
  • the processor 601 is specifically configured to process, according to the second preset formula, a gender probability that each sample user is a male, and a number of sample users, to generate a proportion of the male user, the second The default formula is: Determining 1- ⁇ as the proportion of female users in the sample set;
  • the processor 601 processes the gender probability of each sample user as a male, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user based on a third preset formula to generate male user access.
  • the probability of the male application interface, the third preset formula is: Where S represents the total number of application interfaces accessed by each sample user;
  • the processor 601 processes, according to the fourth preset formula, the gender probability of each sample user as a male, the number of female application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user, to generate male user access.
  • the probability of the female application interface, the fourth preset formula is:
  • the processor 601 processes the gender probability of each sample user as a female, the number of male user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user based on the fifth preset formula to generate female user access.
  • the probability of the male application interface, the fifth preset formula is:
  • the processor 601 processes the gender probability of each sample user as a female, the number of female user application interfaces accessed by each sample user, and the total number of application interfaces accessed by each sample user based on the sixth preset formula to generate female user access.
  • the probability of the female application interface, the sixth preset formula is:
  • the processor 601 is further configured to perform the following steps:
  • the type of the application interface accessed by the sample user is determined according to the set of the male application interface set and the female application interface set.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • the processor 601 is specifically configured to perform the following steps:
  • the current user is a male gender probability greater than a preset probability threshold, identifying the current user as a male; or
  • the current user is identified as a female.
  • the gender probability of the current user includes: a gender probability of the current user being a male, and a gender probability that the current user is a female;
  • the processor 601 is specifically configured to perform the following steps:
  • the gender probability of the current user being a male is greater than the gender probability of the current user being a female, identifying the current user as a male;
  • the current user is identified as a female.
  • the processor 601 is further configured to perform the following steps:
  • the electronic device in the embodiment of the present application constructs a sample set according to the number of application interfaces of various types accessed by the sample user, and generates a gender ratio distribution parameter and an access probability distribution parameter by training the sample set, and uses the generated sex ratio.
  • the distribution parameter and the access probability distribution parameter identify the current user's gender, and realize the automatic identification of the user's gender.
  • the accuracy of the recognition result can be ensured. Provide an effective reference for gender-based services.
  • the electronic device 600 may further include: a display 603, a radio frequency circuit 604, an audio circuit 605, and a power source 606.
  • the display 603, the radio frequency circuit 604, the audio circuit 605, and the power source 606 are electrically connected to the processor 601, respectively.
  • the display 603 can be used to display information entered by a user or information provided to a user, as well as various graphical user interfaces, which can be composed of graphics, text, icons, video, and any combination thereof.
  • the display 603 can include a display panel.
  • the display panel can be configured in the form of a liquid crystal display (LCD) or an organic light-emitting diode (OLED).
  • LCD liquid crystal display
  • OLED organic light-emitting diode
  • the radio frequency circuit 604 can be used for transceiving radio frequency signals to establish wireless communication with network devices or other electronic devices through wireless communication, and to transmit and receive signals with network devices or other electronic devices.
  • the audio circuit 605 can be used to provide an audio interface between a user and an electronic device through a speaker or a microphone.
  • the power source 606 can be used to power various components of the electronic device 600.
  • the power source 606 can be logically coupled to the processor 601 through a power management system to enable functions such as managing charging, discharging, and power management through the power management system.
  • the electronic device 600 may further include a camera, a Bluetooth module, and the like, and details are not described herein again.
  • the embodiment of the present application further provides a storage medium, where the storage medium stores a computer program, and when the computer program runs on a computer, causes the computer to perform the user gender identification method in any of the above embodiments, such as: Constructing a sample set according to a type of an application interface accessed by the sample user, the sample of the sample set includes a quantity of each sample user accessing the male class application interface and a number of each sample user accessing the female class application interface; Performing training to generate a gender ratio distribution parameter and an access probability distribution parameter; using the gender ratio distribution parameter and the access probability distribution parameter, and the number of current user access male application interfaces and the number of current user access female application interfaces, Describe the gender probability of the current user; and identify the gender of the current user according to the gender probability of the current user.
  • the storage medium may be a magnetic disk, an optical disk, a read only memory (ROM), or a random access memory (RAM).
  • ROM read only memory
  • RAM random access memory
  • the computer program may be stored in a computer readable storage medium, such as in a memory of the electronic device, and executed by at least one processor in the electronic device, and may include, for example, user gender during execution.
  • the storage medium may be a magnetic disk, an optical disk, a read only memory, a random access memory, or the like.
  • each functional module may be integrated into one processing chip, or each module may exist physically separately, or two or more modules may be integrated into one module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
  • the integrated module if implemented in the form of a software functional module and sold or used as a standalone product, may also be stored in a computer readable storage medium, such as a read only memory, a magnetic disk or an optical disk, etc. .

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Abstract

本申请实施例公开了一种用户性别识别方法、装置、存储介质及电子设备，其中，用户性别识别方法包括：根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；根据所述当前用户的性别概率识别所述当前用户的性别。

Description

用户性别识别方法、装置、存储介质及电子设备
本申请要求于2017年10月31日提交中国专利局、申请号为201711047061.3、发明名称为“用户性别识别方法、装置、存储介质及电子设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及通信技术领域，具体涉及一种用户性别识别方法、装置、存储介质及电子设备。
背景技术
随着科技的发展，手机等电子设备越来越普及，电子设备的智能程度越来越高，目前的电子设备已能够自动地为用户提供一些服务，而电子设备在为用户提供有些服务时，通常希望知道用户的性别，以根据用户的性别提供相应的服务。
技术解决方案
本申请实施例提供了一种用户性别识别方法、装置、存储介质及电子设备，能够自动识别用户的性别。
第一方面，本申请实施例提供的用户性别识别方法，包括：
根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
根据所述当前用户的性别概率识别所述当前用户的性别。
第二方面，本申请实施例提供的用户性别识别装置，包括：
建立单元，用于根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
训练单元，用于对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
生成单元，用于利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
识别单元，用于根据所述当前用户的性别概率识别所述当前用户的性别。
第三方面，本申请实施例提供的存储介质，其上存储有计算机程序，当所述计算机程序在计算机上运行时，使得所述计算机执行如本申请实施例第一方面所述的用户性别识别方法。
第四方面，本申请实施例提供的电子设备，包括处理器和存储器，所述存储器有计算机程序，所述处理器通过调用所述计算机程序，用于执行如本申请实施例第一方面所述的用户性别识别方法。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例提供的用户性别识别方法的应用场景示意图。
图2是本申请实施例提供的用户性别识别方法的流程示意图。
图3是本申请实施例提供的各种分布参数的生成方法的流程示意图。
图4是本申请实施例提供的用户性别识别方法的另一流程示意图。
图5是本申请实施例提供的用户性别识别装置的结构示意图。
图6是本申请实施例提供的用户性别识别装置的另一结构示意图。
图7是本申请实施例提供的电子设备的结构示意图。
图8是本申请实施例提供的电子设备的另一结构示意图。
本发明的实施方式
请参照图式，其中相同的组件符号代表相同的组件，本申请的原理是以实施在一适当的运算环境中来举例说明。以下的说明是基于所例示的本申请具体实施例，其不应被视为限制本申请未在此详述的其它具体实施例。
现有技术中，当电子设备需要知道用户的性别时，往往需要用户主动提供性别，例如：通过页面请求用户手动输入性别，涉及用户隐私，智能程度不够，用户体验欠佳，因而，本申请实施例提供了一种用户性别识别方法，能够自动识别用户的性别，本申请实施例提供的用户性别识别方法，包括以下步骤：
根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
根据所述当前用户的性别概率识别所述当前用户的性别。
一实施例中，对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数，包括：
初始时，为所述样本集随机给定性别比例分布参数和访问概率分布参数；
根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；
根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；
重复执行上述两个步骤，直至前后两次得到的对应参数的差值小于预设参数阈值时，输出性别比例分布参数和访问概率分布参数。
一实施例中，根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率，包括：
根据所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；
根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
一实施例中，基于第一预设公式对所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量进行处理，生成每个样本用户为男性的性别概率，所述第一预设公式为：
Figure PCTCN2018110476-appb-000001
其中，j∈[1，n]，n表示样本用户的数量，u j表示样本用户j为男性的性别概率，α表示所述样本集中男性用户所占的比例，1-α表示所述样本集中女性用户所占的比例，p (1)表示男性用户访问男性类应用界面的概率，p (2)表示男性用户访问女性类应用界面的概率，q (1)表示女性用户访问男性类应用界面的概率，q (2)表示女性用户访问女性类应用界面的概率，
Figure PCTCN2018110476-appb-000002
表示样本用户j访问男性类应用界面的数量，
Figure PCTCN2018110476-appb-000003
表示样本用户j访问女性类应用界面的数量；将1-u j确定为样本用户j为女性的性别概率。
一实施例中，根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数，包括：
根据每个样本用户为男性的性别概率以及样本用户的数量，生成男性用户所占的比例；
根据男性用户所占的比例，确定女性用户所占的比例；
根据每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问男性类应用界面的概率；
根据每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问女性类应用界面的概率；
根据每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问男性类应用界面的概率；
根据每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问女性类应用界面的概率。
一实施例中，基于第二预设公式对每个样本用户为男性的性别概率，以及样本用户的数量进行处理，生成男性用户所占的比例，所述第二预设公式为：
Figure PCTCN2018110476-appb-000004
将1-α确定为女性用户所占的比例；
基于第三预设公式对每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问男性类应用界面的概率，所述第三预设公式为：
Figure PCTCN2018110476-appb-000005
其中，S表示每个样本用户访问的应用界面的总数；
基于第四预设公式对每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问女性类应用界面的概率，所述第四预设公式为：
Figure PCTCN2018110476-appb-000006
基于第五预设公式对每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问男性类应用界面的概率，所述第五预设公式为：
Figure PCTCN2018110476-appb-000007
基于第六预设公式对每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问女性类应用界面的概率，所述第六预设公式为：
Figure PCTCN2018110476-appb-000008
一实施例中，所述方法还包括：
设置男性类应用界面集及女性类应用界面集；
根据设置的男性类应用界面集及女性类应用界面集，确定样本用户访问的应用界面的类型。
一实施例中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
根据所述当前用户的性别概率识别所述当前用户的性别，包括：
若所述当前用户为男性的性别概率大于预设概率阈值，则将所述当前用户识别为男性；或者
若所述当前用户为女性的性别概率大于所述预设概率阈值，则将所述当前用户识别为女性。
一实施例中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
根据所述当前用户的性别概率识别所述当前用户的性别，包括：
若所述当前用户为男性的性别概率大于所述当前用户为女性的性别概率，则将所述当前用户识别为男性；或者
若所述当前用户为女性的性别概率大于所述当前用户为男性的性别概率，则将所述当前用户识别为女性。
一实施例中，所述方法还包括：
根据所述当前用户的性别识别结果为所述当前用户推送信息或应用程序。
本申请实施例提供的用户性别识别方法，其执行主体可以是本申请实施例提供的用户性别识别装置，或者集成了该用户性别识别装置的电子设备，其中该用户性别识别装置可以采用硬件或者软件的方式实现。其中，电子设备可以是智能手机、平板电脑、掌上电脑、笔记本电脑、或者台式电脑等设备。
请参阅图1，图1为本申请实施例提供的用户性别识别方法的应用场景示意图，以用户性别识别装置为电子设备为例，电子设备可以从服务器获取样本用户访问的应用界面的相关数据，例如：样本用户访问的应用界面的图片、文字、排版、声音等数据，样本用户可以是未知性别的用户；根据获取的数据确定样本用户访问的应用界面的类型，根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率，所述当前用户的性别概率包括当前用户为男性的性别概率，以及当前用户为女性的性别概率；根据所述当前用户的性别概率识别所述当前用户的性别。比如：生成的当前用户为男性的性别概率为0.8，当前用户为女性的性别概率为0.2，当前用户为男性的概率大于当前用户为女性的概率，则将当前用户识别为男性。
本申请实施例将从用户性别识别装置的角度，描述本申请实施例提供的用户性别识别方法，该用户性别识别装置具体可以集成在电子设备中。该用户性别识别方法包括：根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；根据所述当前用户的性别概率识别所述当前用户的性别。
在一优选实施例中，提供了一种用户性别识别方法，如图2所示，本实施例提供的用户性别识别方法的具体流程可以如下：
步骤S201、根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量。
通常来说，男性用户访问的应用界面与女性用户访问的应用界面是存在一定区别的，男性用户访问的应用界面偏男性化，而女性用户访问的应用界面偏女性化。例如：男性用户通常会访问偏男性化的游戏应用(如地下城、反恐精英等)界面、偏男性话的小说(如军事、历史小说)界面、偏男性话的频道(如体育、汽车频道)界面，偏男性化的购物界面(如男装)；而女性用户通常会访问偏女性化的游戏应用(如化妆系列、装扮系列游戏)界面、偏女性话的小说(如言情、魔幻小说)界面、偏女性话的频道(如娱乐、八卦频道)界面，偏女性化的购物界面(如女装、化妆品)等。
本实施例中，为了识别用户的性别，可以设置两个类型的应用界面集：男性类应用界面集和女性类应用界面集。男性类应用界面集中可以包括各种偏男性化的应用界面，或者包括各种偏男性化的应用界面的特征信息；女性类应用界面集中可以包括各种偏女性化的应用界面，或者包括各种偏女性化的应用界面的特征信息。
具体实现中，可以根据设置的男性类应用界面集和女性类应用界面集，确定样本用户访问的应用界面的类型。例如：样本用户访问的应用界面属于男性类应用界面集，则将该应用界面的类型确定为男性类应用界面；反之，如果样本用户访问的应用界面属于女性类应用界面集，则将该应用界面的类型确定为女性类应用界面。例如：样本用户访问的应用界面的特征信息与男性类应用界面集中的特征信息匹配，则将该应用界面的类型确定为男性类应用界面；反之，如果样本用户访问的应用界面的特征信息与女性类应用界面集中的特征信息匹配，则将该应用界面的类型确定为女性类应用界面。
具体地，电子设备可以从服务器获取样本用户访问的应用界面的相关数据，然后根据设置的男性类应用界面集和女性类应用界面集确定样本用户访问的应用界面的类型。比如，服务器可以在历史时间段内，按照预设频率，从各个电子设备收集各个样本用户最近连续访问的预设数量的应用界面的相关数据，将收集的数据发送给需要进行用户性别识别的电子设备。应用界面的相关数据可以包括但不限于：应用界面的图片、文字、排版、声音等数据。历史时间段可以是，例如过去3天；预设频率可以是，例如每个小时；预设数量可以是，例如1000；样本用户的数量为多个，例如可以为100。
电子设备确定每个样本用户访问的预设数量的应用界面中，男性类应用界面及女性类应用界面的数量，根据确定的数量构建样本集。样本集的一个样本中，包括一个样本用户访问的预设数量的应用界面中，男性类应用界面的数量及女性类应用界面的数量。例如，用x (1)表示一个样本用户访问的男性类应用界面的数量，用x (2)表示一个样本用户访问的女性类应用界面的数量，则一个样本中将包括x (1)，x (2)这两个特征。
假如：样本用户的数量为n，则样本集可如下表1所示：
Figure PCTCN2018110476-appb-000009
表1
需要说明的是，本实施例所提及的样本用户可以是未知性别的用户，因此，不需要样本用户主动提供自己的性别，不涉及用户隐私，每个样本没有性别标签。
步骤S202、对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数。
性别比例分布参数指的是，各种性别所占的比例值。性别比例分布参数包括：男性用户所占的比例(可用α表示)和女性用户所占的比例(可用1-α表示)。
访问概率分布参数指的是，各种性别的用户访问各类应用界面的概率。访问概率分布参数包括：男性用户访问男性类应用界面的概率(可用p (1)表示)、男性用户访问女性类应用界面的概率(可用p (2)表示)、女性用户访问男性类应用界面的概率(可用q (1)表示)、女性用户访问女性类应用界面的概率 (可用q (2)表示)。两类参数可如下表2所示：
Figure PCTCN2018110476-appb-000010
表2
对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数的过程，可参阅图3所示，包括以下步骤：
步骤S2021、初始时，为样本集随机给定性别比例分布参数和访问概率分布参数；
即初始时，随机给定α、1-α、p (1)、p (2)、q (1)、q (2)的值，由于每个参数表示比例或概率，因此，每个参数的给值范围为(0，1)，且满足p (1)+p (2)≤a，q (1)+q (2)≤1-a。例如：给定α、1-α、p (1)、p (2)、q (1)、q (2)的值分别为0.5、0.5、0.2、0.05、0.06、0.3。
步骤S2022、根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；
即根据所述样本集中男性用户所占的比例α、女性用户所占的比例1-α、男性用户访问男性类应用界面的概率p (1)、男性用户访问女性类应用界面的概率p (2)、女性用户访问男性类应用界面的概率q (1)、女性用户访问女性类应用界面的概率q (2)，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
具体地，可以采用第一预设公式对所述样本集中男性用户所占的比例α、女性用户所占的比例1-α、男性用户访问男性类应用界面的概率p (1)、男性用户访问女性类应用界面的概率p (2)、女性用户访问男性类应用界面的概率q (1)、女性用户访问女性类应用界面的概率q (2)，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量进行处理，生成每个样本用户为男性的性别概率，所述第一预设公式为：
Figure PCTCN2018110476-appb-000011
其中，j∈[1，n]，u j表示样本用户j为男性的性别概率，
Figure PCTCN2018110476-appb-000012
表示样本用户j访问男性类应用界面的数量，
Figure PCTCN2018110476-appb-000013
表示样本用户j访问女性类应用界面的数量；将1-u j确定为样本用户j为女性的性别概率。
步骤S2023、根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；
即可以根据每个样本用户为男性的性别概率u j，以及样本用户的数量n，生成男性用户所占的比例α。
具体地，可以采用第二预设公式对每个样本用户为男性的性别概率u j，以及样本用户的数量n进行处理，生成男性用户所占的比例α，所述第二预设公式为：
Figure PCTCN2018110476-appb-000014
根据男性用户所占的比例α，确定女性用户所占的比例。具体地，可以将1-α确定为女性用户所占的比例。
根据每个样本用户为男性的性别概率u j、每个样本用户访问男性类应用界面的数量
Figure PCTCN2018110476-appb-000015
以及每个样本用户访问的应用界面的总数S，生成男性用户访问男性类应用界面的概率p (1)。
具体地，可以采用第三预设公式对每个样本用户为男性的性别概率u j、每个样本用户访问男性类应用界面的数量
Figure PCTCN2018110476-appb-000016
以及每个样本用户访问的应用界面的总数S进行处理，生成男性用户访问男性类应用界面的概率p (1)，所述第三预设公式为：
Figure PCTCN2018110476-appb-000017
根据每个样本用户为男性的性别概率u j、每个样本用户访问女性类应用界面的数量
Figure PCTCN2018110476-appb-000018
以及每个样本用户访问的应用界面的总数S，生成男性用户访问女性类应用界面的概率p (2)。
具体地，可以利用第四预设公式对每个样本用户为男性的性别概率u j、每个样本用户访问女性类应用界面的数量
Figure PCTCN2018110476-appb-000019
以及每个样本用户访问的应用界面的总数S进行处理，生成男性用户访问女性类应用界面的概率p (2)，所述第四预设公式为：
Figure PCTCN2018110476-appb-000020
根据每个样本用户为女性的性别概率1-u j、每个样本用户访问男性类应用界面的数量
Figure PCTCN2018110476-appb-000021
以及每个样本用户访问的应用界面的总数S，生成女性用户访问男性类应用界面的概率q (1)。
具体地，可以利用第五预设公式对每个样本用户为女性的性别概率1-u j、每个样本用户访问男性类应用界面的数量
Figure PCTCN2018110476-appb-000022
以及每个样本用户访问的应用界面的总数S进行处理，生成女性用户访问男性 类应用界面的概率q (1)，所述第五预设公式为：
Figure PCTCN2018110476-appb-000023
根据每个样本用户为女性的性别概率1-u j、每个样本用户访问女性类应用界面的数量
Figure PCTCN2018110476-appb-000024
以及每个样本用户访问的应用界面的总数S，生成女性用户访问女性类应用界面的概率q (2)。
具体地，可以利用第六预设公式对每个样本用户为女性的性别概率1-u j、每个样本用户访问女性类应用界面的数量
Figure PCTCN2018110476-appb-000025
以及每个样本用户访问的应用界面的总数S进行处理，生成女性用户访问女性类应用界面的概率q (2)，所述第六预设公式为：
Figure PCTCN2018110476-appb-000026
步骤S2024、判断前后两次得到的对应参数的差值是否小于预设参数阈值，若是，则执行步骤S2025，否则，返回步骤S2022；
预设参数阈值可根据实际需要自定义取值，例如：可以取0.001。
具体实现中，每次执行完步骤S2023之后，可以计算前后两次得到的对应参数的差值的绝对值，若对应参数的差值的绝对值不小于预设参数阈值，则返回步骤S2022，继续迭代，直至对应参数的差值的绝对值均小于预设参数阈值时，停止迭代。
步骤S2025、输出性别比例分布参数和访问概率分布参数。
即输出α、1-α、p (1)、p (2)、q (1)、q (2)这六个参数。
图3所示，即为采用最大期望算法(Expectation Maximization Algorithm，EM)得到各个概率分布参数的过程，其中步骤S2022即为EM算法的E步，步骤S2023即为EM算法的M步。实际应用中，可以不断地采集样本用户访问应用界面的相关数据，以对样本集进行更新，从而更新对应的概率分布参数，以获得更加准确的识别结果。
在某些实施方式中，步骤S2021至步骤S2025可以预先在服务器中完成。例如，服务器可以对样本集进行训练，得到各个概率分布参数，将得到的概率分布参数发送给需要进行性别识别的电子设备，电子设备根据得到的各个概率分布参数识别某个用户的性别。
步骤S203、利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率。
比如：当前用户为i，当前用户为当前电子设备的用户，可以采集当前用户最近访问的预设数量的应用界面，统计预设数量的应用界面中，男性类应用界面的数量
Figure PCTCN2018110476-appb-000027
以及女性类应用界面的数量
Figure PCTCN2018110476-appb-000028
利用第七预设公式生成当前用户为男性的性别概率u i，所述第七预设公式为：
Figure PCTCN2018110476-appb-000029
则，当前用户为女性的性别概率为1-u i。
步骤S204、根据所述当前用户的性别概率识别所述当前用户的性别。
例如，可以判断u i与1-u i的大小，若u i大于1-u i，则将当前用户识别为男性；反之，若u i小于1-u i，则将当前用户识别为女性。
识别出当前用户的性别之后，可以根据性别为当前用户做一些信息或应用程序的推送。例如：当识别出当前用户为男性的时候，可以给当前用户推送一些适合男性玩的新游戏，当识别出当前用户为女性的时候，可以给当前用户推送一些化妆品促销信息等，当然，还可以根据识别出的性别做一些其他的优化，此处不做具体限定。
本实施例中，可以根据样本用户访问的各个类型的应用界面的数量构建样本集，通过对样本集进行训练生成性别比例分布参数和访问概率分布参数，利用生成的性别比例分布参数和访问概率分布参数，识别当前用户的性别，实现了用户性别的自动识别；通过对样本集进行训练得到各种分布参数，进而进行用户性别识别的方法，能够保证识别结果的准确性，为基于性别的服务提供了有效的参考依据。
在一优选实施例中，提供了另一种用户性别识别方法，如图4所示，本实施例将以采集100个样本用户最近访问的1000个应用界面构建样本集，以识别电子设备的当前用户的性别为例，进行说明，本实施例的方法包括：
步骤S401、设置男性类应用界面集及女性类应用界面集。
用户的性别包括：男和女。为了识别用户的性别，本实施例中，可以设置两个类型的应用界面集：男性类应用界面集和女性类应用界面集。男性类应用界面集中可以包括各种偏男性化的应用界面，或者包括各种偏男性化的应用界面的特征信息；女性类应用界面集中可以包括各种偏女性化的应用界面，或者包括各种偏女性化的应用界面的特征信息。
步骤S402、根据设置的男性类应用界面集及女性类应用界面集，确定样本用户访问的应用界面的类型。
例如：样本用户访问的应用界面属于男性类应用界面集，则将该应用界面的类型确定为男性类应用界面；反之，如果样本用户访问的应用界面属于女性类应用界面集，则将该应用界面的类型确定为女性类应用界面。
例如：样本用户访问的应用界面的特征信息与男性类应用界面集中的特征信息匹配，则将该应用界面的类型确定为男性类应用界面；反之，如果样本用户访问的应用界面的特征信息与女性类应用界面集中的特征信息匹配，则将该应用界面的类型确定为女性类应用界面。
具体地，电子设备可以从服务器获取样本用户访问的应用界面的相关数据，然后根据设置的男性类应用界面集和女性类应用界面集确定样本用户访问的应用界面的类型。比如，服务器可以在历史时间段内，按照预设频率，从100电子设备收集100样本用户最近连续访问的1000个应用界面的相关数据，将收集的数据发送给需要进行用户性别识别的电子设备。应用界面的相关数据可以包括但不限于：应用界面的图片、文字、排版、声音等数据。历史时间段可以是，例如过去3天；预设频率可以是，例如每个小时。
步骤S403、根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量。
电子设备确定每个样本用户最近连续访问的1000个应用界面中，男性类应用界面及女性类应用界面的数量，根据确定的数量构建样本集。样本集中包括100个样本，一个样本中，包括一个样本用户最近连续访问的1000个应用界面中，男性类应用界面的数量及女性类应用界面的数量。例如，用x (1)表示一个样本用户访问的男性类应用界面的数量，用x (2)表示一个样本用户访问的女性类应用界面的数量，则一个样本中将包括x (1)，x (2)这两个特征。100个样本构成的样本集可以表示为：
Figure PCTCN2018110476-appb-000030
需要说明的是，本实施例所提及的100个样本用户可以是未知性别的用户，因此，不需要样本用户主动提供自己的性别，不涉及用户隐私，每个样本没有性别标签。
步骤S404、对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数。
性别比例分布参数指的是，各种性别所占的比例值。性别比例分布参数包括：男性用户所占的比例(可用α表示)和女性用户所占的比例(可用1-α表示)。
访问概率分布参数指的是，各种性别的用户访问各类应用界面的概率。访问概率分布参数包括：男性用户访问男性类应用界面的概率(可用p (1)表示)、男性用户访问女性类应用界面的概率(可用p (2)表示)、女性用户访问男性类应用界面的概率(可用q (1)表示)、女性用户访问女性类应用界面的概率(可用q (2)表示)。
训练的目的，即得到α、1-α、p (1)、p (2)、q (1)、q (2)，具体的训练过程，可参阅上述实施例的描述，此处不再赘述。
具体在本实施例中，
Figure PCTCN2018110476-appb-000031
Figure PCTCN2018110476-appb-000032
步骤S405、利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率。
比如：当前用户为i，当前用户为当前电子设备的用户，可以采集当前用户最近访问的1000个应用界面，统计1000个应用界面中，男性类应用界面的数量
Figure PCTCN2018110476-appb-000033
以及女性类应用界面的数量
Figure PCTCN2018110476-appb-000034
利用第七预设公式生成当前用户为男性的性别概率u i，所述第七预设公式为：
Figure PCTCN2018110476-appb-000035
则，当前用户为女性的性别概率为1-u i。
步骤S406、判断当前用户为男性的性别概率是否大于预设概率阈值，若大于，则执行步骤S407，否则，执行步骤S408。
步骤S407、将当前用户识别为男性。
步骤S408、判断当前用户为女性的性别概率是否大于预设概率阈值，若大于，则执行步骤S409，否则结束处理。
步骤S409、将当前用户识别为男性。
预设概率阈值可根据实际需求自定义取值，例如可以取0.8、0.85等。
即可以判断u i或1-u i是否大于预设概率阈值，若u i大于预设概率阈值，则将当前用户识别为男性，若1-u i大于预设概率阈值，则将当前用户识别为女性。
另外，还可以直接通过判断u i与1-u i的大小来识别当前用户的性别。比如：若u i大于1-u i，则将当前用户识别为男性，若u i小于1-u i，则将当前用户识别为女性。
另外，如果u i和1-u i均不大于预设概率阈值，也可以采用比较u i和1-u i的大小的方法来识别当前用户的性别。或者，在u i和1-u i均不大于预设概率阈值时，重新采集样本数据重新构建样本集，以更新各个概率分布参数，然后重新计算当前用户的性别概率；或者在u i和1-u i均不大于预设概率阈值时，重新采集当前用户的应用界面访问数据，以重新计算当前用户的性别概率。
识别出当前用户的性别之后，可以根据性别为当前用户做一些信息或应用程序的推送。例如：当识别出当前用户为男性的时候，可以给当前用户推送一些体育直播信息，当识别出当前用户为女性的时候，可以给当前用户推送一些娱乐动态信息等，当然，还可以根据识别出的性别做一些其他的优化，此处不做具体限定。
本实施例中，可以根据样本用户访问的各个类型的应用界面的数量构建样本集，通过对样本集进行训练生成性别比例分布参数和访问概率分布参数，利用生成的性别比例分布参数和访问概率分布参数，识别当前用户的性别，实现了用户性别的自动识别；通过对样本集进行训练得到各种分布参数，进而进行用户性别识别的方法，能够保证识别结果的准确性，为基于性别的服务提供了有效的参考依据。
本申请实施例还提供了一种用户性别识别装置，包括建立单元、训练单元、生成单元及识别单元，如下：
建立单元，用于根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
训练单元，用于对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
生成单元，用于利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
识别单元，用于根据所述当前用户的性别概率识别所述当前用户的性别。
一实施例中，所述训练单元包括：
初始化子单元，用于在初始时，为所述样本集随机给定性别比例分布参数和访问概率分布参数；
生成子单元，用于根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；所述生成子单元重复执行上述两个步骤，直至前后两次得到的对应参数的差值小于预设参数阈值时，输出性别比例分布参数和访问概率分布参数。
一实施例中，所述生成子单元根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率，包括：
所述生成子单元根据所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；及
所述生成子单元根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
一实施例中，所述生成子单元根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数，包括：
所述生成子单元根据每个样本用户为男性的性别概率以及样本用户的数量，生成男性用户所占的比例；
所述生成子单元根据男性用户所占的比例，确定女性用户所占的比例；
所述生成子单元根据每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问男性类应用界面的概率；
所述生成子单元根据每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问女性类应用界面的概率；
所述生成子单元根据每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问男性类应用界面的概率；
所述生成子单元根据每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问女性类应用界面的概率。
一实施例中，所述装置还包括：
设置单元，用于设置男性类应用界面集及女性类应用界面集；
确定单元，用于根据设置的男性类应用界面集及女性类应用界面集，确定样本用户访问的应用界面的类型。
一实施例中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
所述识别单元具体用于：
在所述当前用户为男性的性别概率大于预设概率阈值时，将所述当前用户识别为男性；或者在所述当前用户为女性的性别概率大于所述预设概率阈值时，将所述当前用户识别为女性。
一实施例中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
所述识别单元具体用于：
在所述当前用户为男性的性别概率大于所述当前用户为女性的性别概率时，将所述当前用户识别为男性；或者在所述当前用户为女性的性别概率大于所述当前用户为男性的性别概率时，将所述当前用户识别为女性。
一实施例中，所述装置还包括：
推送单元，用于根据所述当前用户的性别识别结果为所述当前用户推送信息或应用程序。
在一优选实施例中，还提供一种用户性别识别装置，该用户性别识别装置应用于电子设备，如图5所示，该用户性别识别装置包括：建立单元501、训练单元502、生成单元503和识别单元504，如下：
建立单元501，用于根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
训练单元502，用于对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
生成单元503，用于利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
识别单元504，用于根据所述当前用户的性别概率识别所述当前用户的性别。
在一些实施例中，如图6所示，训练单元502包括：初始化子单元5021和生成子单元5022，如下：
初始化子单元5021，用于在初始时，为所述样本集随机给定性别比例分布参数和访问概率分布参数；
生成子单元5022，用于根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；所述生成子单元5022重 复执行上述两个步骤，直至前后两次得到的对应参数的差值小于预设参数阈值时，输出性别比例分布参数和访问概率分布参数。
在一些实施例中，所述生成子单元5022根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率，包括：
所述生成子单元5022根据所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；及
所述生成子单元5022根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
在一些实施例中，所述生成子单元5022基于第一预设公式对所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量进行处理，生成每个样本用户为男性的性别概率，所述第一预设公式为：
Figure PCTCN2018110476-appb-000036
其中，j∈[1，n]，n表示样本用户的数量，u j表示样本用户j为男性的性别概率，α表示所述样本集中男性用户所占的比例，1-α表示所述样本集中女性用户所占的比例，p (1)表示男性用户访问男性类应用界面的概率，p (2)表示男性用户访问女性类应用界面的概率，q (1)表示女性用户访问男性类应用界面的概率，q (2)表示女性用户访问女性类应用界面的概率，
Figure PCTCN2018110476-appb-000037
表示样本用户j访问男性类应用界面的数量，
Figure PCTCN2018110476-appb-000038
表示样本用户j访问女性类应用界面的数量；
所述生成子单元5022将1-u j确定为样本用户j为女性的性别概率。
在一些实施例中，所述生成子单元5022根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数，包括：
所述生成子单元5022根据每个样本用户为男性的性别概率以及样本用户的数量，生成男性用户所占的比例；
所述生成子单元5022根据男性用户所占的比例，确定女性用户所占的比例；
所述生成子单元5022根据每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问男性类应用界面的概率；
所述生成子单元5022根据每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问女性类应用界面的概率；
所述生成子单元5022根据每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成所述样本集中女性用户访问男性类应用界面的概率；
所述生成子单元5022根据每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问女性类应用界面的概率。
在一些实施例中，所述生成子单元5022基于第二预设公式对每个样本用户为男性的性别概率，以 及样本用户的数量进行处理，生成男性用户所占的比例，所述第二预设公式为：
Figure PCTCN2018110476-appb-000039
所述生成子单元5022将1-α确定为女性用户所占的比例；
所述生成子单元5022基于第三预设公式对每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问男性类应用界面的概率，所述第三预设公式为：
Figure PCTCN2018110476-appb-000040
其中，S表示每个样本用户访问的应用界面的总数；
所述生成子单元5022基于第四预设公式对每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问女性类应用界面的概率，所述第四预设公式为：
Figure PCTCN2018110476-appb-000041
所述生成子单元5022基于第五预设公式对每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问男性类应用界面的概率，所述第五预设公式为：
Figure PCTCN2018110476-appb-000042
所述生成子单元5022基于第六预设公式对每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问女性类应用界面的概率，所述第六预设公式为：
Figure PCTCN2018110476-appb-000043
在一些实施例中，如图6所示，所述装置还包括设置单元505和确定单元506，如下：
设置单元505，用于设置男性类应用界面集及女性类应用界面集；
确定单元506，用于根据设置的男性类应用界面集及女性类应用界面集，确定样本用户访问的应用界面的类型。
在一些实施例中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
所述识别单元504具体用于：
在所述当前用户为男性的性别概率大于预设概率阈值时，将所述当前用户识别为男性；或者在所述当前用户为女性的性别概率大于所述预设概率阈值时，将所述当前用户识别为女性。
在一些实施例中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
所述识别单元504具体用于：
在所述当前用户为男性的性别概率大于所述当前用户为女性的性别概率时，将所述当前用户识别为男性；或者在所述当前用户为女性的性别概率大于所述当前用户为男性的性别概率时，将所述当前用户识别为女性。
在一些实施例中，如图6所示，所述装置还包括：
推送单元507，用于根据所述当前用户的性别识别结果为所述当前用户推送信息或应用程序。
需要说明的是，本实施例提供的用户性别识别装置在进行用户性别识别时，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。另外，上述实施例提供的用户性别识别装置与用户性别识别方法属于同一构思，其具体实现过程详见方法实施例，此处不再赘述。
由上可知，本实施例采用在电子设备中，由建立单元501根据样本用户访问的各个类型的应用界面的数量构建样本集，训练单元502通过对样本集进行训练生成性别比例分布参数和访问概率分布参数，生成单元503利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率，识别单元504根据所述当前用户的性别概率识别所述当前用户的性别，实现了用户性别的自动识别；通过对样本集进行训练得到各种分布参数，进而进行用户性别识别的方法，能够保证识别结果的准确性，为基于性别的服务提供了有效的参考依据。
本申请实施例还提供一种电子设备。请参阅图7，电子设备600包括处理器601以及存储器602。其中，处理器601与存储器602电性连接。
所述处理器600是电子设备600的控制中心，利用各种接口和线路连接整个电子设备的各个部分，通过运行或加载存储在存储器602内的计算机程序，以及调用存储在存储器602内的数据，执行电子设备600的各种功能并处理数据，从而对电子设备600进行整体监控。
所述存储器602可用于存储软件程序以及模块，处理器601通过运行存储在存储器602的计算机程序以及模块，从而执行各种功能应用以及数据处理。存储器602可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的计算机程序(比如声音播放功能、图像播放功能等)等；存储数据区可存储根据电子设备的使用所创建的数据等。此外，存储器602可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。相应地，存储器602还可以包括存储器控制器，以提供处理器601对存储器602的访问。
在本申请实施例中，电子设备600中的处理器601会按照如下的步骤，将一个或一个以上的计算机程序的进程对应的指令加载到存储器602中，并由处理器601运行存储在存储器602中的计算机程序，从而实现各种功能，如下：
根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
根据所述当前用户的性别概率识别所述当前用户的性别。
在某些实施方式中，对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数时，处理器601具体执行以下步骤：
初始时，为所述样本集随机给定性别比例分布参数和访问概率分布参数；
根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；
根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；
重复执行上述两个步骤，直至前后两次得到的对应参数的差值小于预设参数阈值时，输出性别比例分布参数和访问概率分布参数。
在某些实施方式中，根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率时，处理器601具体执行以下步骤：
根据所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；
根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
在某些实施方式中，处理器601具体用于基于第一预设公式对所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量进行处理，生成每个样本用户为男性的性别概率，所述第一预设公式为：
Figure PCTCN2018110476-appb-000044
其中，j∈[1，n]，n表示样本用户的数量，u j表示样本用户j为男性的性别概率，α表示所述样本集中男性用户所占的比例，1-α表示所述样本集中女性用户所占的比例，p (1)表示男性用户访问男性类应用界面的概率，p (2)表示男性用户访问女性类应用界面的概率，q (1)表示女性用户访问男性类应用界面的概率，q (2)表示女性用户访问女性类应用界面的概率，
Figure PCTCN2018110476-appb-000045
表示样本用户j访问男性类应用界面的数量，
Figure PCTCN2018110476-appb-000046
表示样本用户j访问女性类应用界面的数量；
处理器601将1-u j确定为样本用户j为女性的性别概率。
在某些实施方式中，根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数时，处理器601具体用于执行以下步骤：
根据每个样本用户为男性的性别概率以及样本用户的数量，生成男性用户所占的比例；
根据所述样本集中男性用户所占的比例，确定女性用户所占的比例；
根据每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问男性类应用界面的概率；
根据每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问女性类应用界面的概率；
根据每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问男性类应用界面的概率；
根据每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成所述样本集中女性用户访问女性类应用界面的概率。
在某些实施方式中，处理器601具体用于基于第二预设公式对每个样本用户为男性的性别概率，以及样本用户的数量进行处理，生成男性用户所占的比例，所述第二预设公式为：
Figure PCTCN2018110476-appb-000047
将1-α确定为所述样本集中女性用户所占的比例；
处理器601基于第三预设公式对每个样本用户为男性的性别概率、每个样本用户访问男性类应用界 面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问男性类应用界面的概率，所述第三预设公式为：
Figure PCTCN2018110476-appb-000048
其中，S表示每个样本用户访问的应用界面的总数；
处理器601基于第四预设公式对每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问女性类应用界面的概率，所述第四预设公式为：
Figure PCTCN2018110476-appb-000049
处理器601基于第五预设公式对每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问男性类应用界面的概率，所述第五预设公式为：
Figure PCTCN2018110476-appb-000050
处理器601基于第六预设公式对每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问女性类应用界面的概率，所述第六预设公式为：
Figure PCTCN2018110476-appb-000051
在某些实施方式中，处理器601还用于执行以下步骤：
设置男性类应用界面集及女性类应用界面集；
根据设置的男性类应用界面集及女性类应用界面集，确定样本用户访问的应用界面的类型。
在某些实施方式中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
根据所述当前用户的性别概率识别所述当前用户的性别时，处理器601具体用于执行以下步骤：
若所述当前用户为男性的性别概率大于预设概率阈值，则将所述当前用户识别为男性；或者
若所述当前用户为女性的性别概率大于所述预设概率阈值，则将所述当前用户识别为女性。
在某些实施方式中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
根据所述当前用户的性别概率识别所述当前用户的性别时，处理器601具体用于执行以下步骤：
若所述当前用户为男性的性别概率大于所述当前用户为女性的性别概率，则将所述当前用户识别为男性；或者
若所述当前用户为女性的性别概率大于所述当前用户为男性的性别概率，则将所述当前用户识别为女性。
在某些实施方式中，处理器601还用于执行以下步骤：
根据所述当前用户的性别识别结果为所述当前用户推送信息或应用程序。
由上述可知，本申请实施例的电子设备，根据样本用户访问的各个类型的应用界面的数量构建样本 集，通过对样本集进行训练生成性别比例分布参数和访问概率分布参数，利用生成的性别比例分布参数和访问概率分布参数，识别当前用户的性别，实现了用户性别的自动识别；通过对样本集进行训练得到各种分布参数，进而进行用户性别识别的方法，能够保证识别结果的准确性，为基于性别的服务提供了有效的参考依据。
请一并参阅图8，在某些实施方式中，电子设备600还可以包括：显示器603、射频电路604、音频电路605以及电源606。其中，其中，显示器603、射频电路604、音频电路605以及电源606分别与处理器601电性连接。
所述显示器603可以用于显示由用户输入的信息或提供给用户的信息以及各种图形用户接口，这些图形用户接口可以由图形、文本、图标、视频和其任意组合来构成。显示器603可以包括显示面板，在某些实施方式中，可以采用液晶显示器(Liquid Crystal Display，LCD)、或者有机发光二极管(Organic Light-Emitting Diode，OLED)等形式来配置显示面板。
所述射频电路604可以用于收发射频信号，以通过无线通信与网络设备或其他电子设备建立无线通讯，与网络设备或其他电子设备之间收发信号。
所述音频电路605可以用于通过扬声器、传声器提供用户与电子设备之间的音频接口。
所述电源606可以用于给电子设备600的各个部件供电。在一些实施例中，电源606可以通过电源管理系统与处理器601逻辑相连，从而通过电源管理系统实现管理充电、放电、以及功耗管理等功能。
尽管图8中未示出，电子设备600还可以包括摄像头、蓝牙模块等，在此不再赘述。
本申请实施例还提供一种存储介质，所述存储介质存储有计算机程序，当所述计算机程序在计算机上运行时，使得所述计算机执行上述任一实施例中的用户性别识别方法，比如：根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；根据所述当前用户的性别概率识别所述当前用户的性别。
在本申请实施例中，存储介质可以是磁碟、光盘、只读存储器(Read Only Memory，ROM，)、或者随机存取记忆体(Random Access Memory，RAM)等。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述的部分，可以参见其他实施例的相关描述。
需要说明的是，对本申请实施例的用户性别识别方法而言，本领域普通决策人员可以理解实现本申请实施例的用户性别识别方法的全部或部分流程，是可以通过计算机程序来控制相关的硬件来完成，所述计算机程序可存储于一计算机可读取存储介质中，如存储在电子设备的存储器中，并被该电子设备内的至少一个处理器执行，在执行过程中可包括如用户性别识别方法的实施例的流程。其中，所述的存储介质可为磁碟、光盘、只读存储器、随机存取记忆体等。
对本申请实施例的用户性别识别装置而言，其各功能模块可以集成在一个处理芯片中，也可以是各个模块单独物理存在，也可以两个或两个以上模块集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中，所述存储介质譬如为只读存储器，磁盘或光盘等。
以上对本申请实施例所提供的一种用户性别识别方法、装置、存储介质及电子设备进行了详细介绍，本文中应用了具体个例对本申请的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本申请的方法及其核心思想；同时，对于本领域的技术人员，依据本申请的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本申请的限制。

Claims (20)

  1. 一种用户性别识别方法，其中，包括：
    根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
    对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
    利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
    根据所述当前用户的性别概率识别所述当前用户的性别。
  2. 根据权利要求1所述的用户性别识别方法，其中，对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数，包括：
    初始时，为所述样本集随机给定性别比例分布参数和访问概率分布参数；
    根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；
    根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；
    重复执行上述两个步骤，直至前后两次得到的对应参数的差值小于预设参数阈值时，输出性别比例分布参数和访问概率分布参数。
  3. 根据权利要求2所述的用户性别识别方法，其中，根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率，包括：
    根据所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；
    根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
  4. 根据权利要求3所述的用户性别识别方法，其中，
    基于第一预设公式对所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量进行处理，生成每个样本用户为男性的性别概率，所述第一预设公式为：
    Figure PCTCN2018110476-appb-100001
    其中，j∈[1，n]，n表示样本用户的数量，u j表示样本用户j为男性的性别概率，α表示所述样本集中男性用户所占的比例，1-α表示所述样本集中女性用户所占的比例，p (1)表示男性用户访问男性类应用界面的概率，p (2)表示男性用户访问女性类应用界面的概率，q (1)表示女性用户访问男性类应用界面的概率，q (2)表示女性用户访问女性类应用界面的概率，
    Figure PCTCN2018110476-appb-100002
    表示样本用户j访问男性类应用界面的数量，
    Figure PCTCN2018110476-appb-100003
    表示样本用户j访问女性类应用界面的数量；
    将1-u j确定为样本用户j为女性的性别概率。
  5. 根据权利要求4所述的用户性别识别方法，其中，根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数，包括：
    根据每个样本用户为男性的性别概率以及样本用户的数量，生成男性用户所占的比例；
    根据男性用户所占的比例，确定女性用户所占的比例；
    根据每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问男性类应用界面的概率；
    根据每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问女性类应用界面的概率；
    根据每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问男性类应用界面的概率；
    根据每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问女性类应用界面的概率。
  6. 根据权利要求5所述的用户性别识别方法，其中，
    基于第二预设公式对每个样本用户为男性的性别概率，以及样本用户的数量进行处理，生成男性用户所占的比例，所述第二预设公式为：
    Figure PCTCN2018110476-appb-100004
    将1-α确定为女性用户所占的比例；
    基于第三预设公式对每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问男性类应用界面的概率，所述第三预设公式为：
    Figure PCTCN2018110476-appb-100005
    其中，S表示每个样本用户访问的应用界面的总数；
    基于第四预设公式对每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成男性用户访问女性类应用界面的概率，所述第四预设公式为：
    Figure PCTCN2018110476-appb-100006
    基于第五预设公式对每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问男性类应用界面的概率，所述第五预设公式为：
    Figure PCTCN2018110476-appb-100007
    基于第六预设公式对每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数进行处理，生成女性用户访问女性类应用界面的概率，所述第六预设公式为：
    Figure PCTCN2018110476-appb-100008
  7. 根据权利要求1至6任意一项所述的用户性别识别方法，其中，所述方法还包括：
    设置男性类应用界面集及女性类应用界面集；
    根据设置的男性类应用界面集及女性类应用界面集，确定样本用户访问的应用界面的类型。
  8. 根据权利要求1至6任意一项所述的用户性别识别方法，其中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
    根据所述当前用户的性别概率识别所述当前用户的性别，包括：
    若所述当前用户为男性的性别概率大于预设概率阈值，则将所述当前用户识别为男性；或者
    若所述当前用户为女性的性别概率大于所述预设概率阈值，则将所述当前用户识别为女性。
  9. 根据权利要求1至6任意一项所述的用户性别识别方法，其中，所述当前用户的性别概率包括：所述当前用户为男性的性别概率，以及所述当前用户为女性的性别概率；
    根据所述当前用户的性别概率识别所述当前用户的性别，包括：
    若所述当前用户为男性的性别概率大于所述当前用户为女性的性别概率，则将所述当前用户识别为男性；或者
    若所述当前用户为女性的性别概率大于所述当前用户为男性的性别概率，则将所述当前用户识别为女性。
  10. 根据权利要求1至6任意一项所述的用户性别识别方法，其中，所述方法还包括：
    根据所述当前用户的性别识别结果为所述当前用户推送信息或应用程序。
  11. 一种用户性别识别装置，其中，包括：
    建立单元，用于根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
    训练单元，用于对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
    生成单元，用于利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
    识别单元，用于根据所述当前用户的性别概率识别所述当前用户的性别。
  12. 根据权利要求11所述的用户性别识别装置，其中，所述训练单元包括：
    初始化子单元，用于在初始时，为所述样本集随机给定性别比例分布参数和访问概率分布参数；
    生成子单元，用于根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；所述生成子单元重复执行上述两个步骤，直至前后两次得到的对应参数的差值小于预设参数阈值时，输出性别比例分布参数和访问概率分布参数。
  13. 根据权利要求12所述的用户性别识别装置，其中，所述生成子单元根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率，包括：
    所述生成子单元根据所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；及
    所述生成子单元根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
  14. 根据权利要求13所述的用户性别识别装置，其中，所述生成子单元根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数，包括：
    所述生成子单元根据每个样本用户为男性的性别概率以及样本用户的数量，生成男性用户所占的比例；
    所述生成子单元根据男性用户所占的比例，确定女性用户所占的比例；
    所述生成子单元根据每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问男性类应用界面的概率；
    所述生成子单元根据每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问女性类应用界面的概率；
    所述生成子单元根据每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问男性类应用界面的概率；
    所述生成子单元根据每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问女性类应用界面的概率。
  15. 一种存储介质，其上存储有计算机程序，其中，当所述计算机程序在计算机上运行时，使得所述计算机执行如权利要求1至10任一项所述的用户性别识别方法。
  16. 一种电子设备，包括处理器和存储器，所述存储器有计算机程序，其中，所述处理器通过调用所述计算机程序，从而执行以下步骤：
    根据样本用户访问的应用界面的类型构建样本集，所述样本集的样本中包括每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量；
    对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数；
    利用所述性别比例分布参数和访问概率分布参数，以及当前用户访问男性类应用界面的数量和当前用户访问女性类应用界面的数量，生成所述当前用户的性别概率；
    根据所述当前用户的性别概率识别所述当前用户的性别。
  17. 根据权利要求16所述的电子设备，其中，在对所述样本集进行训练，生成性别比例分布参数和访问概率分布参数时，所述处理器具体用于执行以下步骤：
    初始时，为所述样本集随机给定性别比例分布参数和访问概率分布参数；
    根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率；
    根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数；
    重复执行上述两个步骤，直至前后两次得到的对应参数的差值小于预设参数阈值时，输出性别比例分布参数和访问概率分布参数。
  18. 根据权利要求17所述的电子设备，其中，在根据当前的性别比例分布参数和访问概率分布参数，以及每个样本用户访问男性类应用界面的数量和每个样本用户访问女性类应用界面的数量，生成每个样本用户的性别概率时，所述处理器具体用于执行以下步骤：
    根据所述样本集中男性用户所占的比例、女性用户所占的比例、男性用户访问男性类应用界面的概率、男性用户访问女性类应用界面的概率、女性用户访问男性类应用界面的概率、女性用户访问女性类应用界面的概率，以及每个样本用户访问男性类应用界面的数量、每个样本用户访问女性类应用界面的数量，生成每个样本用户为男性的性别概率；
    根据每个样本用户为男性的性别概率，确定每个样本用户为女性的性别概率。
  19. 根据权利要求18所述的电子设备，其中，在根据每个样本用户的性别概率，生成性别比例分布参数和访问概率分布参数时，所述处理器具体用于执行以下步骤：
    根据每个样本用户为男性的性别概率以及样本用户的数量，生成男性用户所占的比例；
    根据男性用户所占的比例，确定女性用户所占的比例；
    根据每个样本用户为男性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问男性类应用界面的概率；
    根据每个样本用户为男性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成男性用户访问女性类应用界面的概率；
    根据每个样本用户为女性的性别概率、每个样本用户访问男性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问男性类应用界面的概率；
    根据每个样本用户为女性的性别概率、每个样本用户访问女性类应用界面的数量、以及每个样本用户访问的应用界面的总数，生成女性用户访问女性类应用界面的概率。
  20. 根据权利要求16至19任意一项所述的电子设备，其中，所述处理器还用于执行以下步骤：
    设置男性类应用界面集及女性类应用界面集；
    根据设置的男性类应用界面集及女性类应用界面集，确定样本用户访问的应用界面的类型。
PCT/CN2018/110476 2017-10-31 2018-10-16 用户性别识别方法、装置、存储介质及电子设备 WO2019085743A1 (zh)

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