CN116549970A - Information processing method and device in game, electronic equipment and storage medium - Google Patents

Abstract

The application provides an information processing method, an information processing device, electronic equipment and a storage medium in a game, wherein the method comprises the following steps: determining a first characterization value of the first account number in the first game, wherein the first characterization value corresponds to each game feature in the plurality of game features; determining a second characterization value of the second account number in the second game, wherein the second characterization value corresponds to each game feature respectively; determining a mapping index between the first account number and the second account number based on the feature evaluation index of each game feature according to the determined first characterization value and second characterization value; based on the determined mapping index, attribution of the first account and the second account is predicted. By the method and the device, data fusion can be facilitated.

Description

Information processing method and device in game, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of computer applications, and in particular, to a method and apparatus for processing information in a game, an electronic device, and a storage medium.

Background

In real life, players may participate in multiple games simultaneously or intermittently, that is, there may be multiple virtual game characters associated between different games or within the same game.

Currently, in different games, the relevance between accounts used by players is generally determined based on the account names (or game nicknames) used by the players in the games, and if the players use different account names, the relevance between the accounts cannot be effectively judged. Alternatively, the association between the accounts used by the players may also be determined based on the internet protocol (Internet Protocol, IP) address of the player terminal, but there is a deviation in this manner.

The above judgment method cannot effectively fuse data, which results in scattered distribution of players in the game.

Disclosure of Invention

In view of this, embodiments of the present application provide at least a method, an apparatus, an electronic device, and a storage medium for processing information in a game, which can facilitate data fusion.

In a first aspect, exemplary embodiments of the present application provide an information processing method in a game, the method including: determining a first characterization value of the first account number in the first game, wherein the first characterization value corresponds to each game feature in the plurality of game features; determining a second characterization value of the second account number in the second game, wherein the second characterization value corresponds to each game feature respectively; determining a mapping index between the first account number and the second account number based on the feature evaluation index of each game feature according to the determined first characterization value and second characterization value; based on the determined mapping index, attribution of the first account and the second account is predicted.

In one possible implementation, the first account is a game account registered in a first game, the second account is a game account registered in a second game, the first game and the second game are the same game, or the first game and the second game are different games.

In a possible implementation manner, the first characterization value and the second characterization value are each used for characterizing the corresponding game feature in a numerical form, and/or the plurality of game features include a numerical game feature and a non-numerical game feature, wherein the characterization value corresponding to each non-numerical game feature is determined based on an attribute value which is extracted from the non-numerical game feature and can be described numerically, or is determined based on an encoding value of the non-numerical game feature, and the encoding value is obtained by encoding the non-numerical game feature in a unified encoding manner in each game.

In one possible embodiment, the method may further include: and carrying out normalization processing on the characterization value corresponding to each game feature so as to determine the feature evaluation index of each game feature based on the characterization value after normalization processing.

In one possible implementation, the feature evaluation index of each game feature may include a feature distance determined according to a first feature value and a second feature value corresponding to the game feature.

In one possible implementation, the mapping index between the first account number and the second account number may be determined by: determining characteristic influence coefficients corresponding to the game characteristics respectively; and determining a mapping index between the first account number and the second account number according to the feature distance of each game feature and the corresponding feature influence coefficient.

In a possible implementation manner, the attribution may be used to indicate whether the first account number and the second account number are mapped to the same natural person, where the method may further include: if the attribution of the first account and the second account is predicted to be indicative of the same natural person, attribution labels are added to the first account and the second account at the same time, and the attribution labels are used for representing that the two associated accounts are attributed to the same natural person.

In one possible embodiment, the step of predicting attribution of the first account and the second account based on the determined mapping index may include: comparing the mapping index with a preset threshold value; if the mapping index is not smaller than the preset threshold, the first account and the second account are predicted to be mapped to the same natural person; if the mapping index is smaller than the preset threshold, the first account and the second account are predicted not to be mapped to the same natural person.

In one possible implementation, the preset threshold may be determined by: acquiring a plurality of training samples, wherein each training sample comprises a test account number and a characterization value of the test account number corresponding to each game feature; determining a plurality of test mapping indexes based on the characterization values corresponding to the test account numbers; selecting a plurality of candidate thresholds, and determining account attribution results under each candidate threshold based on the plurality of test mapping indexes; determining sample prediction evaluation indexes for the plurality of training samples under each candidate threshold based on the determined account attribution result; and selecting a target candidate threshold from the plurality of candidate thresholds as the preset threshold according to the determined sample prediction evaluation index.

In one possible implementation, account attribution results at each candidate threshold may be obtained by: and comparing each test mapping index with the candidate threshold value, determining that two accounts corresponding to the test mapping index are not mapped to the same natural person according to the test mapping index smaller than the candidate threshold value, and determining that two accounts corresponding to the test mapping index are mapped to the same natural person according to the test mapping index not smaller than the candidate threshold value.

In one possible implementation, based on the determined account attribution result, the step of determining a sample predictive rating index for the plurality of training samples at each candidate threshold may include: for each candidate threshold, determining the precision rate and recall rate corresponding to the training samples under the candidate threshold according to the account attribution result under the candidate threshold; and determining a sample prediction evaluation index under each candidate threshold according to the precision rate and the recall rate under each candidate threshold.

In one possible implementation manner, the preset threshold may be a candidate threshold corresponding to the maximum sample prediction evaluation index.

In a second aspect, embodiments of the present application further provide an information processing apparatus in a game, the apparatus including: the first numerical value determining module is used for determining a first characterization value of the first account corresponding to each game feature in the plurality of game features in the first game; the second value determining module is used for determining a second characterization value of the second account corresponding to each game feature in a second game; the mapping determining module is used for determining a mapping index between the first account number and the second account number based on the characteristic evaluation index of each game characteristic according to the determined first characteristic value and second characteristic value; and the attribution prediction module predicts attributions of the first account and the second account based on the determined mapping index.

In a third aspect, embodiments of the present application further provide an electronic device, including: a processor, a memory and a bus, the memory storing machine readable instructions executable by the processor, the processor and the memory in communication via the bus when the electronic device is running, the machine readable instructions when executed by the processor performing the steps of the method of information processing in a game in any one of the possible implementations of the first aspect or the first aspect.

In a fourth aspect, the embodiments of the present application further provide a computer readable storage medium, on which a computer program is stored, which when executed by a processor performs the steps of the method for processing information in a game in the first aspect or any of the possible implementation manners of the first aspect.

The information processing method, the device, the electronic equipment and the storage medium in the game are beneficial to improving the effectiveness of data fusion.

In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered limiting the scope, and that other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flowchart showing an information processing method in a game provided in an exemplary embodiment of the present application;

FIG. 2 shows a flowchart of steps provided by an exemplary embodiment of the present application for determining a mapping coefficient between a first account and a second account;

FIG. 3 shows a flowchart of steps provided by an exemplary embodiment of the present application to determine a preset threshold;

FIG. 4 is a flowchart illustrating steps provided by exemplary embodiments of the present application for determining a sample predictive rating index at each candidate threshold;

fig. 5 is a schematic diagram showing the structure of an information processing apparatus in a game provided in an exemplary embodiment of the present application;

fig. 6 shows a schematic structural diagram of an electronic device according to an exemplary embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it should be understood that the accompanying drawings in the present application are only for the purpose of illustration and description, and are not intended to limit the protection scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. A flowchart, as used in this application, illustrates operations implemented according to some embodiments of the present application. It should be appreciated that the operations of the flow diagrams may be implemented out of order and that steps without logical context may be performed in reverse order or concurrently. Moreover, one or more other operations may be added to the flow diagrams and one or more operations may be removed from the flow diagrams as directed by those skilled in the art.

The terms "a," "an," "the," and "said" are used in this specification to denote the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. in addition to the listed elements/components/etc.; the terms "first" and "second" and the like are used merely as labels, and are not intended to limit the number of their objects.

It should be understood that in embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or" is merely an association relationship describing an association object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. "comprising A, B and/or C" means comprising any 1 or any 2 or 3 of A, B, C.

It should be understood that in the embodiments of the present application, "B corresponding to a", "a corresponding to B", or "B corresponding to a", means that B is associated with a, from which B may be determined. Determining B from a does not mean determining B from a alone, but may also determine B from a and/or other information.

In addition, the described embodiments are only some, but not all, of the embodiments of the present application. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application.

In practice, players may participate in multiple games simultaneously or intermittently, i.e., there may be multiple natural persons in the same game that are coincident between different games or within the same game.

At present, the identity of a player is often determined by the account name (or game nickname) used by the player in a game, but if the player uses a different account name, effective judgment cannot be performed. Moreover, the same account name is not generally allowed to appear within the same game or under the same server, which also easily results in failure of identification of each player.

In addition, the account number used by each player can be judged based on the IP address of the player terminal, but the judgment mode is too simple, and the IP address may have a certain deviation, so that the judgment result is not accurate enough.

Based on the above conventional judgment methods, effective data fusion cannot be performed, resulting in scattered distribution of players in the game. In addition, account management is difficult to carry out according to the relevance among players, operation loss is easy to cause, manpower is large, and pushing efficiency is low.

In view of at least one aspect of the foregoing, the present application proposes an information processing method, apparatus, electronic device, and storage medium in a game, capable of determining a mapping relationship between accounts through a plurality of game feature data of different accounts in the game, so as to predict attribution of each account.

First, the names involved in the embodiments of the present application will be briefly described.

In the embodiment of the application, a graphical user interface may be provided through the terminal device, and at least part of a virtual scene of the game is displayed in the graphical user interface, wherein:

terminal equipment:

the terminal device in the embodiment of the present application mainly refers to an intelligent device that is used for providing a game interface (presenting a game scene in the game interface) and is capable of performing control operation on a virtual character, and the terminal device may include, but is not limited to, any one of the following devices: smart phones, tablet computers, portable computers, desktop computers, gaming machines, personal Digital Assistants (PDAs), electronic book readers, MP4 (Moving Picture Experts Group Audio Layer IV, dynamic image experts compression standard audio layer 4) players, and the like. The terminal device has installed and running therein an application program supporting a game scene, such as an application program supporting a three-dimensional game scene. The application may include, but is not limited to, any of a virtual reality application, a three-dimensional map application, a military simulation application, a MOBA game, a multiplayer gunfight survival game, a Third party shooting game (TPS, third-Personal Shooting Game). Alternatively, the application may be a stand-alone application, such as a stand-alone 3D game, or a network-on-line application.

Graphical user interface:

is an interface display format in which a person communicates with a computer, allowing a user to manipulate icons, marks, or menu options on a screen using an input device such as a mouse or a keyboard, and also allowing a user to manipulate icons or menu options on a screen by performing a touch operation on a touch screen of a touch terminal to select a command, start a program, or perform some other task, etc.

Virtual scene:

is a virtual scene that an application displays (or provides) when running on a terminal or server. Optionally, the virtual scene is a simulation environment for the real world, or a semi-simulated semi-fictional virtual environment, or a purely fictional virtual environment. The virtual scene is any one of a two-dimensional virtual scene and a three-dimensional virtual scene, and the virtual environment can be sky, land, ocean and the like, wherein the land comprises environmental elements such as deserts, cities and the like. The virtual scene is a scene of a complete game logic of a user control virtual character.

Virtual roles:

refers to a virtual character in a virtual environment, which may be a virtual character manipulated by a player, including but not limited to at least one of a virtual character, a virtual animal, a cartoon character, and may also be a non-player-manipulated virtual character (NPC). Alternatively, when the virtual environment is a three-dimensional virtual environment, the virtual characters may be three-dimensional virtual models, each having its own shape and volume in the three-dimensional virtual environment, occupying a part of the space in the three-dimensional virtual environment. Optionally, the virtual character is a three-dimensional character constructed based on three-dimensional human skeleton technology, which implements different external figures by wearing different skins. In some implementations, the avatar may also be implemented using a 2.5-dimensional or 2-dimensional model, which is not limited by embodiments of the present application.

There may be multiple virtual characters in the virtual scene, which are virtual characters that the player manipulates (i.e., characters that the player controls through the input device), or artificial intelligence (Artificial Intelligence, AI) set in the virtual environment combat through training. Optionally, the avatar is a avatar that plays in the game scene. Optionally, the number of virtual characters in the game scene fight is preset, or is dynamically determined according to the number of terminal devices joining the virtual fight, which is not limited in the embodiment of the present application. In one possible implementation, a user can control a virtual character to move in the virtual scene, e.g., control the virtual character to run, jump, crawl, etc., and also control the virtual character to fight other virtual characters using virtual skills, virtual props, etc., provided by an application.

A player may register one or more game accounts with the same game. For example, each game account may be bound to a fixed virtual character in the game, where each time a player enters the game, the player participates in the game using the virtual character bound to the registered game account. Or when each game account number enters a game, the server randomly allocates a corresponding virtual role for each game account number participating in the virtual fight of the game, and the player uses the randomly allocated virtual role to participate in the game in the virtual fight of the game.

Game interface:

the interface is an interface corresponding to the application program provided or displayed through a graphical user interface, and the interface comprises a UI interface and a game screen for the player to interact. In alternative embodiments, game controls (e.g., skill controls, movement controls, functionality controls, etc.), indication identifiers (e.g., direction indication identifiers, character indication identifiers, etc.), information presentation areas (e.g., number of defeaters, time of play, etc.), or game setting controls (e.g., system settings, stores, gold coins, etc.) may be included in the UI interface. In an alternative embodiment, the game screen may be a display screen corresponding to the virtual scene displayed by the terminal device, may be a game interface for viewing a virtual task in the game, or may be a parameter configuration interface in a game preparation stage, and the display screen corresponding to the virtual scene may include virtual objects such as a game character, an NPC character, and an AI character for executing game logic in the virtual scene.

In an alternative embodiment, the terminal device may be a local terminal device. Taking a game as an example, the local terminal device stores a game program and is used to present a game screen. The local terminal device is used for interacting with the player through the graphical user interface, namely, conventionally downloading and installing the game program through the electronic device and running. The manner in which the local terminal device provides the graphical user interface to the player may include a variety of ways, for example, it may be rendered for display on a display screen of the terminal device, or provided to the player by holographic projection. For example, the local terminal device may include a display screen for presenting a graphical user interface including a game scene screen and a processor for running the game, generating the graphical user interface, and controlling the display of the graphical user interface on the display screen.

Application scenarios applicable to the application are introduced. The method and the device can be applied to the technical field of games, and in the games, a plurality of players participating in the games join in the same virtual fight together.

Before entering the virtual game, the player may select different character attributes, e.g., identity attributes, for the virtual characters in the virtual game by assigning the different character attributes to determine different camps, so that the player wins the game play by performing the assigned tasks of the game at different stages of the virtual game, e.g., multiple virtual characters having the character attribute a "culls" the virtual character having the character attribute B at the stages of the game play to obtain the winning of the game play. Here, when entering the virtual game, a character attribute may be randomly assigned to each virtual character participating in the virtual game.

The implementation environment provided in one embodiment of the present application may include: the system comprises a first terminal device, a server and a second terminal device. The first terminal device and the second terminal device are respectively communicated with the server to realize data communication. In this embodiment, the first terminal device and the second terminal device are respectively installed with an application program for executing the in-game information processing method provided by the present application, and the server is a server side for executing the in-game information processing method provided by the present application. The first terminal device and the second terminal device can communicate with the server respectively through the application program.

Taking a first terminal device as an example, the first terminal device establishes communication with a server by running an application. In an alternative embodiment, the server establishes the virtual game according to the game request of the application program. The parameters of the virtual game may be determined according to the parameters in the received game request, for example, the parameters of the virtual game may include the number of persons participating in the virtual game, the role level of participating in the virtual game, and the like. When the first terminal equipment receives a response of the game server, displaying a game scene corresponding to the virtual game through a graphical user interface of the first terminal equipment, wherein the first terminal equipment is equipment controlled by a first user, the virtual character displayed in the graphical user interface of the first terminal equipment is a player character (namely a first virtual character) controlled by the first user, and the first user inputs an operation instruction through the graphical user interface so as to control the player character to execute corresponding operation in the game scene.

Taking a second terminal device as an example, the second terminal device establishes communication with the server by running an application. In an alternative embodiment, the server establishes the virtual game according to the game request of the application program. The parameters of the virtual game may be determined according to the parameters in the received game request, for example, the parameters of the virtual game may include the number of persons participating in the virtual game, the role level of participating in the virtual game, and the like. And when the second terminal equipment receives the response of the server, displaying the game scene corresponding to the virtual game through the graphical user interface of the second terminal equipment. The second terminal device is a device controlled by a second user, the virtual character displayed in the graphical user interface of the second terminal device is a player character controlled by the second user (namely, a second virtual character), and the second user inputs an operation instruction through the graphical user interface so as to control the player character to execute corresponding operation in the virtual scene.

The server calculates data according to game data reported by the first terminal equipment and the second terminal equipment, and synchronizes the calculated game data to the first terminal equipment and the second terminal equipment, so that the first terminal equipment and the second terminal equipment control the graphical user interface to render corresponding game scenes and/or virtual roles according to the synchronous data issued by the game server.

In this embodiment, the first virtual character controlled by the first terminal device and the second virtual character controlled by the second terminal device are virtual characters in the same virtual pair. The first virtual role controlled by the first terminal device and the second virtual role controlled by the second terminal device may have the same role attribute, or may have different role attributes, and the first virtual role controlled by the first terminal device and the second virtual role controlled by the second terminal device may belong to the same camping or may belong to different camps.

It should be noted that, in the virtual game, two or more virtual roles may be included, and different virtual roles may correspond to different terminal devices, that is, in the virtual game, there are two or more terminal devices that perform transmission and synchronization of game data with the game server, respectively.

In order to facilitate understanding of the present application, the method, the device, the electronic device and the storage medium for processing information in a game provided in the embodiments of the present application are described in detail below.

Referring to fig. 1, a flowchart of an information processing method in a game according to an exemplary embodiment of the present application is provided, where the information processing method specifically includes:

step S101: and determining a first characterization value of the first account number in the first game, wherein the first characterization value corresponds to each game feature in the plurality of game features.

Step S102: and determining a second characterization value of the second account number corresponding to each game feature in the second game.

Here, the first account may refer to a game account registered in a first game, the first account being attributed to a first natural person, and the second account may refer to a game account registered in a second game, the second account being attributed to a second natural person.

In the embodiment of the present application, the first game and the second game may be the same game, or the first game and the second game may be different games. In the present application, the game companies to which each game belongs are not limited, that is, the above information processing method may analyze a plurality of games under the same game company, or may analyze a plurality of games under different game companies.

By way of example, the plurality of game features described above may refer to features in different dimensions that relate to a game session.

As an example, the plurality of game features may include, but are not limited to: temporal play characteristics, spatial play characteristics, content play characteristics, and presentation play characteristics. Each game feature is described below as an example.

The temporal gaming characteristic may include a temporal characteristic that reflects the gaming characteristics of the account over time, which may include, by way of example and not limitation, at least one of the following: the method comprises the steps of a time point when a player logs in a game, a time point when the player exits the game, an online time length of each time the player logs in the game, a cost playing time length of the player in the game, a time point of recharging in the game and a game loss time length.

The spatial game features may include spatial features for reflecting the spatial game characteristics of the terminal device held by the player (which may also be referred to as the terminal device logging into the account), and may also refer to hardware configuration parameters of the account during the game process, and may include, by way of example and not limitation, at least one of the following: the method comprises the steps of equipment parameters of terminal equipment of a login account, IP addresses of the terminal equipment of the login account, WIFI data of the terminal equipment of the login account and geographic positions of the terminal equipment of the login account.

The game features on the content may include content features that reflect the social nature of the player within the game, and may also refer to content data generated by the account number within the game, which may include, by way of example and not limitation, at least one of the following: chat information of the account in the game, circles of friends of the account published in the game, number of friends of the account in the game, and number of other players of interest of the account in the game.

The expressive game features may include performance features for reflecting the combat characteristics of the virtual character being played by the player in the game, which may include, by way of example and not limitation, at least one of the following: the number of single-shot defeats (total or average) of an account in a game, the amount of harm an account has in a game, the amount of treatment an account has in a game, the weapons an account uses in a game (e.g., the most frequently used weapons).

That is, the above-mentioned temporal game feature is used to characterize the usage habit of the account for the game, the spatial game feature is used to characterize the hardware configuration of the account when participating in the game, the content game feature is used to characterize the social condition of the account in the game, and the apparent game feature is used to characterize the operation habit of the account in the game stage. It should be appreciated that the above-described game features are game data obtained after user authorization is obtained, and/or may also be game public data obtained from a public platform within the game, and account analysis may be performed in accordance with the above-described game features of at least one dimension in the present application.

Alternatively, the plurality of game features may be selected from one dimension, or may be selected from two or more dimensions, which is not limited in this application.

The plurality of game features participating in step S101 and step S102 may be game features selected from a plurality of game features based on various feature screening methods or in consideration of actual requirements, which is not limited in this application.

In the embodiment of the present application, each game feature corresponds to a characterization value, that is, the game feature corresponds to the characterization value one by one. The game features may be numeric game features and/or non-numeric game features, and the corresponding first and second characterization values are presented in numeric form for facilitating subsequent analysis processes.

For a numeric game feature, the attribute value of the numeric game feature may be directly used as the characterization value.

Taking a numerical game feature as an example of the time length of the player in the game, a specific attribute value (such as 50 minutes) of the time length can be used as a characterization value corresponding to the game feature. Taking the number class game feature as an example of the single-field beat number of the account in the game, a specific attribute value (such as 20 beats) of the single-field beat number can be used as a characterization value corresponding to the game feature.

For non-numeric class game features, the corresponding characterization values may be determined based on predefined transformation rules.

In one example, the characterization value for a non-numeric class game feature may be determined based on a numerically descriptive attribute value extracted from the non-numeric class game feature.

Taking a non-numeric game feature as an example of a circle of friends issued by an account in a game, the number of circles of friends issued in a certain period of time may be determined as a characterization value corresponding to the game feature, or the average number of words of circles of friends issued may be determined as a characterization value corresponding to the game feature.

Taking the chat information of the non-numeric game feature as an account in the game as an example, the average word number of sending single chat entries can be determined as a characterization value corresponding to the game feature, or the number of chat entries sent in a certain period of time can be determined as a characterization value corresponding to the game feature, and the number of keywords (such as 'single row' and 'copy') mentioned in the chat content in a period of time can be determined as the characterization value corresponding to the game feature.

In another example, the characterization value for a non-numeric class game feature may be determined based on the encoded value of the non-numeric class game feature. Here, the code value may be obtained by encoding the non-numeric game feature in a unified encoding manner in each game.

For example, taking a non-numeric game feature as an example of a weapon used in a game by an account, the existing various encoding methods can be utilized to set encoding values for weapons opened in each game in advance, and encoding values of the same weapon in different games are consistent, so as to ensure that the characterization values corresponding to the same weapon are uniform.

Step S103: and determining a mapping index between the first account number and the second account number based on the characteristic evaluation index of each game characteristic according to the determined first characteristic value and the second characteristic value.

Here, for each game feature, the feature evaluation index of the game feature may be determined according to the first feature value and the second feature value corresponding to the game feature, and then the mapping index between the first account number and the second account number may be determined based on the feature evaluation indexes of all the game features.

In a preferred embodiment, the method for processing information in a game of the present application may further include: and carrying out normalization processing on each characterization value to determine a feature evaluation index of each game feature based on the characterization value after normalization processing.

Here, the normalization processing may be performed on each characterization value by using various existing numerical normalization methods, which is not limited in this application. For example, the min-max method may be used for numerical normalization.

In an alternative embodiment, the characterization values may be normalized using the following formula:

in the formula (1), X _new Representing the characterization value after normalization processing, X represents the characterization value corresponding to a game feature, and X _min Representing the minimum value, X, of all characterization values corresponding to a game feature in a target account participating in normalization processing _max And representing the maximum value of each characterization value corresponding to the game feature in the target account participating in the normalization processing.

In one case, the target account involved in the normalization process includes a first account and a second account.

In this case, for each game feature, X may be determined from a first characterization value of the game feature corresponding to a first account and a second characterization value of the game feature corresponding to a second account _min And X _max When normalizing the first characterization value of the game feature, the first characterization value X and the determined X are used for _min And X _max Substituting the first characterization value into the formula (1) to obtain a first characterization value after normalization processing, and repeating the process similarly to obtain a second characterization value after normalization processing.

In another case, the target account involved in the normalization process includes a first account, a second account, and a plurality of reference accounts.

Here, the plurality of reference accounts may include a plurality of accounts having the same account characteristics as the first account and/or the second account. Exemplary account features may include, but are not limited to: account segment digits. For example, for each account in the game, the ranking of each account in the game may be determined based on game data (e.g., combat experience, combat session, combat results) for each account within the game. It should be appreciated that the account features described above may also be other game parameters under an account, as this application is not limited in this regard.

In this case, for each game feature, X may be determined from a plurality of characterization values corresponding to the game feature for the target account (one characterization value corresponding to the game feature for one account) _min And X _max In the pair ofWhen the first characterization value of the game feature is normalized, the first characterization value X and the determined X are processed _min And X _max Substituting the first characterization value into the formula (1) to obtain a first characterization value after normalization processing, and repeating the process similarly to obtain a second characterization value after normalization processing.

In the embodiment of the present application, the feature evaluation index of each game feature is used to evaluate the proximity of the first account and the second account in the aspect of the game feature. By way of example, proximity between accounts may be characterized in this application based on feature distance.

For example, the feature evaluation index of each game feature may include a feature distance determined according to a first characterization value and a second characterization value corresponding to the game feature.

Here, the characteristic distances between the characteristic values may be calculated by using various existing methods for calculating the characteristic distances, which is not limited in this application, and the characteristic distances between the characteristic values may be calculated by using euler distances, which will not be described in detail in this application.

In the embodiment of the application, the mapping index between accounts is used for representing the prediction probability for the attribution consistency between two accounts.

A specific manner of determining the mapping index between the first account number and the second account number will be described below with reference to fig. 2.

Fig. 2 shows a flowchart of the steps for determining a mapping coefficient between a first account number and a second account number provided in an exemplary embodiment of the present application.

Referring to fig. 2, in step S301, feature influence coefficients corresponding to respective game features are determined.

The characteristic influence coefficient is used for representing the influence degree of the corresponding game characteristic on account attribution prediction. In a preferred embodiment, a regression expression may be constructed based on a plurality of training samples to determine coefficients corresponding to respective terms in the regression expression as characteristic influence coefficients.

For example, each training sample may include a test account number and a characterization value of the test account number corresponding to each game feature, where the plurality of test accounts includes a plurality of accounts known to belong to the same physical person and a plurality of accounts known not to belong to the same physical person.

For the characterization value corresponding to each test account, the normalization processing may be performed, and based on the characterization value after the normalization processing, a feature evaluation index (e.g., a feature distance) under each game feature between every two test accounts may be calculated.

In a preferred embodiment of the present application, the mapping relationship between the first account and the second account may be characterized based on a regression expression.

By way of example, the regression expression may be constructed using the following formula:

Y＝α ₁ ·Dis ₁ (X ₁ )+α ₂ ·Dis ₂ (X ₂ )+…+α _n ·Dis _n (X _n )(2)

in the formula (2), Y represents a mapping index between the first account and the second account, and alpha _i Representing the feature influence coefficient, dis, corresponding to the ith game feature _i (X _i ) Representing the ith game feature X _i The corresponding characteristic distance is equal to or greater than 1 and equal to or less than n, wherein n represents the number of game characteristics.

Here, the plurality of training samples may be divided into a plurality of training sets, each training set including two test accounts, and since the mapping relationship between the two test accounts (whether or not it belongs to the same natural person) is known, the mapping index corresponding to the training set in which the mapping relationship belongs to the same natural person may be set to 1, the mapping index corresponding to the training set in which the mapping relationship does not belong to the same natural person may be set to 0, the feature distance may be calculated for the characterization value of each game feature corresponding to the two test accounts in each training set, and substituted into the above formula (2), and the feature influence coefficient α corresponding to each game feature may be obtained by regression training _i 。

In step S302, a mapping index between the first account and the second account is determined according to the feature distance of each game feature and the corresponding feature influence coefficient.

For example, the feature distances of the game features corresponding to the first account and the second account and the determined feature influence coefficients may be substituted into the above formula (2) to obtain the mapping index Y between the first account and the second account.

It should be understood that the above manner of determining the mapping index between accounts is merely an example, and the application is not limited thereto, and the attribution consistency between two accounts may be predicted by other manners.

Returning to fig. 1, step S104: based on the determined mapping index, attribution of the first account and the second account is predicted.

Illustratively, the predicted attribution is used to indicate whether the first account and the second account are mapped to the same natural person. That is, the above processing is to map the account number to a real natural person to determine whether the mapping of the account number is consistent.

For example, the step of predicting attribution of the first account number and the second account number may include: and comparing the determined mapping index with a preset threshold, if the mapping index is not smaller than (greater than or equal to) the preset threshold, predicting that the first account number and the second account number are mapped to the same natural person, and if the mapping index is smaller than the preset threshold, predicting that the first account number and the second account number are not mapped to the same natural person.

Here, the magnitude of the preset threshold can directly affect the prediction result, and a specific value of the preset threshold may be determined based on experience of a person skilled in the art or other means in the present application, which is not limited in this application.

In a preferred embodiment, the specific value of the preset threshold may be determined based on the training result of the training sample, and the specific process of determining the preset threshold is described below with reference to fig. 3.

Fig. 3 shows a flowchart of the steps of determining a preset threshold provided by an exemplary embodiment of the present application.

Referring to fig. 3, in step S105, a plurality of training samples are acquired.

Here, the training samples used in this step may be the same as or different from the training samples used in determining the characteristic influence coefficients, and may be selected by those skilled in the art according to actual situations.

For example, each training sample may include a test account number and a characterization value of the test account number corresponding to each game feature.

In step S106, a plurality of test mapping indexes are determined based on the characterization values corresponding to the test account numbers.

For example, the manner in step S302 described above may be employed to calculate the corresponding test mapping index for each pair of test accounts. This application is not repeated for this portion.

In step S107, a plurality of candidate thresholds are selected, and account attribution results under each candidate threshold are determined based on a plurality of test mapping indexes.

For example, the range of values for the plurality of candidate thresholds may be [0,1], i.e., the plurality of candidate thresholds may be selected from a range of values from 0 to 1.

In a preferred embodiment, account attribution results at each candidate threshold may be obtained by: and comparing each test mapping index with the candidate threshold value, determining that two accounts corresponding to the test mapping index are not mapped to the same natural person according to the test mapping index smaller than the candidate threshold value, and determining that two accounts corresponding to the test mapping index are mapped to the same natural person according to the test mapping index not smaller than the candidate threshold value.

In step S108, a sample prediction evaluation index for a plurality of training samples at each candidate threshold is determined based on the determined account attribution result.

Fig. 4 is a flowchart illustrating steps provided by exemplary embodiments of the present application for determining a sample predictive rating index at each candidate threshold.

Referring to fig. 4, in step S801, for each candidate threshold, the accuracy and recall corresponding to a plurality of training samples under the candidate threshold are determined according to the account attribution result under the candidate threshold.

In this example, a sample predictive rating index for a training sample may be determined based on the precision and recall corresponding to a plurality of training samples.

For example, for each training set, the following data under different candidate thresholds may be counted based on account attribution results: TP: the sample is positive, and the prediction result is positive; FP: the sample is negative, and the prediction result is positive; TN: the sample is negative and the prediction result is negative; FN: the samples are positive and the prediction results are negative.

Based on the statistics, the precision and recall are calculated using the following formulas, respectively:

in the formula (3), P represents the precision rate used to characterize the correct prediction as positive to the total prediction as positive.

In equation (4), R represents the recall rate to characterize the proportion of positive samples correctly predicted to be positive.

In step S802, a sample predictive evaluation index under each candidate threshold is determined according to the precision and recall under each candidate threshold.

For example, the sample predictive evaluation index F1 at each candidate threshold may be determined using the following formula:

returning to fig. 3, in step S109, a target candidate threshold is selected from the plurality of candidate thresholds as a preset threshold according to the determined sample predictive evaluation index.

The preset threshold may be a candidate threshold corresponding to the maximum sample predictive evaluation index.

In one case, a preset threshold is selected based on a sample predictive evaluation index of a scatter-form distribution.

Here, one sample predictive evaluation index corresponds to one candidate threshold, in which case, from among a plurality of sample predictive evaluation indexes distributed in a scattered form, a maximum sample predictive evaluation index is determined, and the candidate threshold corresponding to the maximum sample predictive evaluation index is determined as a preset threshold.

In another case, the preset threshold is selected based on a sample predictive evaluation index curve obtained by fitting.

In this case, the obtained plurality of sample predictive evaluation indexes and the plurality of candidate thresholds may be fitted to obtain a sample predictive evaluation index curve, and a candidate threshold corresponding to the maximum sample predictive evaluation index in the curve is found and determined as a preset threshold.

In an alternative embodiment, the method for processing information in a game of the present application may further include: if the attribution of the first account and the second account is predicted to be indicative of the same natural person, attribution labels are added to the first account and the second account at the same time. Here, the home tag is used to characterize that the two account numbers associated are attributed to the same natural person. For example, an account database corresponding to each game may be established, or a unified account database may be established, where the account database includes at least one account entry, each account entry stores related information corresponding to an account, and the determined attribution tag is added to the account entry corresponding to the account for storage.

If the attribution of the first account and the second account is predicted to be indicative of different natural persons, adding an independent label or not processing. For example, the determined individual tags may also be added to account entries of the corresponding account for storage.

Personalized messages may then be pushed to accounts directed by different tags based on the home tags or the independent tags stored in the account database, e.g., service messages with similar content to accounts of the same home tag, or push messages for other accounts indicated by a certain home tag may be generated based on historical game data for at least one account indicated by the certain home tag. Here, flexible use may be made based on labels stored in the account database, which is not limited in this application.

Based on the information processing method in the game, by mapping each account number in the game, a plurality of virtual roles of which one natural person spans a plurality of games or a plurality of virtual roles in one game can be found, so that the recall rate of account number mapping is improved.

Based on the same application conception, the embodiment of the present application further provides an information processing device in a game corresponding to the method provided in the foregoing embodiment, and since the principle of solving the problem by the device in the embodiment of the present application is similar to that of the information processing method in the game in the foregoing embodiment of the present application, the implementation of the device may refer to the implementation of the method, and the repetition is omitted.

Fig. 5 is a schematic structural view of an information processing apparatus in a game provided in an exemplary embodiment of the present application. As shown in fig. 5, the in-game information processing apparatus 200 includes:

the first numerical value determining module 210 determines a first characterization value of the first account corresponding to each of the plurality of game features in the first game;

the second value determining module 220 determines a second characterization value of the second account corresponding to each game feature in the second game;

the mapping determining module 230 determines a mapping index between the first account number and the second account number based on the feature evaluation index of each game feature according to the determined first characterization value and second characterization value;

the attribution prediction module 240 predicts attributions of the first account and the second account based on the determined mapping index.

In one possible implementation manner of the present application, the first account is a game account registered in a first game, the second account is a game account registered in a second game, the first game and the second game are the same game, or the first game and the second game are different games.

In one possible implementation manner of the present application, the first characterization value and the second characterization value are each used for characterizing the corresponding game feature in a numerical form, and/or the plurality of game features include a numerical game feature and a non-numerical game feature, wherein the characterization value corresponding to each non-numerical game feature is determined based on an attribute value which is extracted from the non-numerical game feature and can be described numerically, or is determined based on an encoding value of the non-numerical game feature, and the encoding value is obtained by encoding the non-numerical game feature in a unified encoding manner in each game.

In one possible implementation of the present application, the mapping determining module 230 performs normalization processing on the characterizing value corresponding to each game feature, so as to determine a feature evaluation index of each game feature based on the characterizing value after normalization processing.

In one possible implementation manner of the present application, the feature evaluation index of each game feature includes a feature distance determined according to a first characterization value and a second characterization value corresponding to the game feature.

In one possible implementation of the present application, the mapping determination module 230 determines the mapping index between the first account number and the second account number by: determining characteristic influence coefficients corresponding to the game characteristics respectively; and determining a mapping index between the first account number and the second account number according to the feature distance of each game feature and the corresponding feature influence coefficient.

In one possible implementation manner of the present application, the attribution is used to indicate whether the first account and the second account are mapped to the same natural person, where if the attribution prediction module 240 predicts that the attribution of the first account and the second account is indicative of the same natural person, an attribution label is added to the first account and the second account at the same time, where the attribution label is used to characterize that the two associated accounts are attributed to the same natural person.

In one possible implementation of the present application, the home prediction module 240 compares the mapping index with a preset threshold; if the mapping index is not smaller than the preset threshold, the first account and the second account are predicted to be mapped to the same natural person; if the mapping index is smaller than the preset threshold, the first account and the second account are predicted not to be mapped to the same natural person.

In one possible implementation of the present application, home prediction module 240 determines the preset threshold by: acquiring a plurality of training samples, wherein each training sample comprises a test account number and a characterization value of the test account number corresponding to each game feature; determining a plurality of test mapping indexes based on the characterization values corresponding to the test account numbers; selecting a plurality of candidate thresholds, and determining account attribution results under each candidate threshold based on the plurality of test mapping indexes; determining sample prediction evaluation indexes for the plurality of training samples under each candidate threshold based on the determined account attribution result; and selecting a target candidate threshold from the plurality of candidate thresholds as the preset threshold according to the determined sample prediction evaluation index.

In one possible implementation of the present application, the attribution prediction module 240 obtains account attribution results at each candidate threshold by: and comparing each test mapping index with the candidate threshold value, determining that two accounts corresponding to the test mapping index are not mapped to the same natural person according to the test mapping index smaller than the candidate threshold value, and determining that two accounts corresponding to the test mapping index are mapped to the same natural person according to the test mapping index not smaller than the candidate threshold value.

In one possible implementation manner of the present application, for each candidate threshold, the attribution prediction module 240 determines, according to the account attribution result under the candidate threshold, the precision rate and recall rate corresponding to the plurality of training samples under the candidate threshold; and determining a sample prediction evaluation index under each candidate threshold according to the precision rate and the recall rate under each candidate threshold.

In one possible implementation manner of the present application, the preset threshold is a candidate threshold corresponding to a maximum sample prediction evaluation index.

In the embodiment of the application, the account numbers are mapped based on the game features, so that the identification efficiency can be improved to a certain extent, and the effective fusion of the data is facilitated.

Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present application. As shown in fig. 6, the electronic device 300 includes a processor 310, a memory 320, and a bus 330.

The memory 320 stores machine readable instructions executable by the processor 310, and when the electronic device 300 is running, the processor 310 communicates with the memory 320 through the bus 330, and when the machine readable instructions are executed by the processor 310, the steps of the information processing method in the game in any of the embodiments described above may be executed, specifically as follows:

determining a first characterization value of the first account number in the first game, wherein the first characterization value corresponds to each game feature in the plurality of game features; determining a second characterization value of the second account number in the second game, wherein the second characterization value corresponds to each game feature respectively; determining a mapping index between the first account number and the second account number based on the feature evaluation index of each game feature according to the determined first characterization value and second characterization value; based on the determined mapping index, attribution of the first account and the second account is predicted.

In one possible implementation manner of the present application, the first account is a game account registered in a first game, the second account is a game account registered in a second game, the first game and the second game are the same game, or the first game and the second game are different games.

In one possible implementation manner of the present application, the first characterization value and the second characterization value are each used for characterizing the corresponding game feature in a numerical form, and/or the plurality of game features include a numerical game feature and a non-numerical game feature, wherein the characterization value corresponding to each non-numerical game feature is determined based on an attribute value which is extracted from the non-numerical game feature and can be described numerically, or is determined based on an encoding value of the non-numerical game feature, and the encoding value is obtained by encoding the non-numerical game feature in a unified encoding manner in each game.

In one possible implementation of the present application, the processor 310 is further configured to perform the following processing: and carrying out normalization processing on the characterization value corresponding to each game feature so as to determine the feature evaluation index of each game feature based on the characterization value after normalization processing.

In one possible implementation manner of the present application, the feature evaluation index of each game feature includes a feature distance determined according to a first characterization value and a second characterization value corresponding to the game feature.

In one possible implementation of the present application, the processor 310 is further configured to determine a mapping index between the first account number and the second account number by: determining characteristic influence coefficients corresponding to the game characteristics respectively; and determining a mapping index between the first account number and the second account number according to the feature distance of each game feature and the corresponding feature influence coefficient.

In a possible embodiment of the present application, the attribution is used to indicate whether the first account number and the second account number are mapped to the same natural person, wherein the processor 310 is further configured to perform the following processing: if the attribution of the first account and the second account is predicted to be indicative of the same natural person, attribution labels are added to the first account and the second account at the same time, and the attribution labels are used for representing that the two associated accounts are attributed to the same natural person.

In one possible implementation of the present application, the processor 310 is further configured to perform the following processing: comparing the mapping index with a preset threshold value; if the mapping index is not smaller than the preset threshold, the first account and the second account are predicted to be mapped to the same natural person; if the mapping index is smaller than the preset threshold, the first account and the second account are predicted not to be mapped to the same natural person.

In one possible implementation of the present application, the processor 310 is further configured to determine the preset threshold by: acquiring a plurality of training samples, wherein each training sample comprises a test account number and a characterization value of the test account number corresponding to each game feature; determining a plurality of test mapping indexes based on the characterization values corresponding to the test account numbers; selecting a plurality of candidate thresholds, and determining account attribution results under each candidate threshold based on the plurality of test mapping indexes; determining sample prediction evaluation indexes for the plurality of training samples under each candidate threshold based on the determined account attribution result; and selecting a target candidate threshold from the plurality of candidate thresholds as the preset threshold according to the determined sample prediction evaluation index.

In one possible implementation of the present application, the processor 310 is further configured to obtain the account attribution result under each candidate threshold by: and comparing each test mapping index with the candidate threshold value, determining that two accounts corresponding to the test mapping index are not mapped to the same natural person according to the test mapping index smaller than the candidate threshold value, and determining that two accounts corresponding to the test mapping index are mapped to the same natural person according to the test mapping index not smaller than the candidate threshold value.

In one possible implementation of the present application, the processor 310 is further configured to perform the following processing: for each candidate threshold, determining the precision rate and recall rate corresponding to the training samples under the candidate threshold according to the account attribution result under the candidate threshold; and determining a sample prediction evaluation index under each candidate threshold according to the precision rate and the recall rate under each candidate threshold.

In one possible implementation manner of the present application, the preset threshold is a candidate threshold corresponding to a maximum sample prediction evaluation index.

In the embodiment of the application, the account numbers are mapped based on the game features, so that the identification efficiency can be improved to a certain extent, and the effective fusion of the data is facilitated.

The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, where the computer program when executed by a processor may perform the steps of the information processing method in a game in any of the foregoing embodiments, specifically as follows:

determining a first characterization value of the first account number in the first game, wherein the first characterization value corresponds to each game feature in the plurality of game features; determining a second characterization value of the second account number in the second game, wherein the second characterization value corresponds to each game feature respectively; determining a mapping index between the first account number and the second account number based on the feature evaluation index of each game feature according to the determined first characterization value and second characterization value; based on the determined mapping index, attribution of the first account and the second account is predicted.

In one possible implementation manner of the present application, the first account is a game account registered in a first game, the second account is a game account registered in a second game, the first game and the second game are the same game, or the first game and the second game are different games.

In one possible implementation manner of the present application, the first characterization value and the second characterization value are each used for characterizing the corresponding game feature in a numerical form, and/or the plurality of game features include a numerical game feature and a non-numerical game feature, wherein the characterization value corresponding to each non-numerical game feature is determined based on an attribute value which is extracted from the non-numerical game feature and can be described numerically, or is determined based on an encoding value of the non-numerical game feature, and the encoding value is obtained by encoding the non-numerical game feature in a unified encoding manner in each game.

In one possible embodiment of the present application, the processor is further configured to perform the following: and carrying out normalization processing on the characterization value corresponding to each game feature so as to determine the feature evaluation index of each game feature based on the characterization value after normalization processing.

In one possible implementation manner of the present application, the feature evaluation index of each game feature includes a feature distance determined according to a first characterization value and a second characterization value corresponding to the game feature.

In one possible embodiment of the present application, the processor is further configured to determine a mapping index between the first account number and the second account number by: determining characteristic influence coefficients corresponding to the game characteristics respectively; and determining a mapping index between the first account number and the second account number according to the feature distance of each game feature and the corresponding feature influence coefficient.

In a possible embodiment of the present application, the attribution is used to indicate whether the first account number and the second account number are mapped to the same natural person, wherein the processor is further configured to perform the following processing: if the attribution of the first account and the second account is predicted to be indicative of the same natural person, attribution labels are added to the first account and the second account at the same time, and the attribution labels are used for representing that the two associated accounts are attributed to the same natural person.

In one possible embodiment of the present application, the processor is further configured to perform the following: comparing the mapping index with a preset threshold value; if the mapping index is not smaller than the preset threshold, the first account and the second account are predicted to be mapped to the same natural person; if the mapping index is smaller than the preset threshold, the first account and the second account are predicted not to be mapped to the same natural person.

In a possible embodiment of the present application, the processor is further configured to determine the preset threshold by: acquiring a plurality of training samples, wherein each training sample comprises a test account number and a characterization value of the test account number corresponding to each game feature; determining a plurality of test mapping indexes based on the characterization values corresponding to the test account numbers; selecting a plurality of candidate thresholds, and determining account attribution results under each candidate threshold based on the plurality of test mapping indexes; determining sample prediction evaluation indexes for the plurality of training samples under each candidate threshold based on the determined account attribution result; and selecting a target candidate threshold from the plurality of candidate thresholds as the preset threshold according to the determined sample prediction evaluation index.

In one possible embodiment of the present application, the processor is further configured to obtain an account attribution result under each candidate threshold by: and comparing each test mapping index with the candidate threshold value, determining that two accounts corresponding to the test mapping index are not mapped to the same natural person according to the test mapping index smaller than the candidate threshold value, and determining that two accounts corresponding to the test mapping index are mapped to the same natural person according to the test mapping index not smaller than the candidate threshold value.

In one possible embodiment of the present application, the processor is further configured to perform the following: for each candidate threshold, determining the precision rate and recall rate corresponding to the training samples under the candidate threshold according to the account attribution result under the candidate threshold; and determining a sample prediction evaluation index under each candidate threshold according to the precision rate and the recall rate under each candidate threshold.

In one possible implementation manner of the present application, the preset threshold is a candidate threshold corresponding to a maximum sample prediction evaluation index.

In the embodiment of the application, the account numbers are mapped based on the game features, so that the identification efficiency can be improved to a certain extent, and the effective fusion of the data is facilitated.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on such understanding, the technical solutions of the present application may be embodied in essence or a part contributing to the prior art or a part of the technical solutions, or in the form of a software product, which is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes or substitutions are covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (15)

1. A method of processing information in a game, the method comprising:

determining a first characterization value of the first account number in the first game, wherein the first characterization value corresponds to each game feature in the plurality of game features;

determining a second characterization value of the second account number in the second game, wherein the second characterization value corresponds to each game feature respectively;

determining a mapping index between the first account number and the second account number based on the feature evaluation index of each game feature according to the determined first characterization value and second characterization value;

based on the determined mapping index, attribution of the first account and the second account is predicted.

2. The method of claim 1, wherein the first account number is a game account number registered in a first game, the second account number is a game account number registered in a second game, the first game and the second game are the same game, or the first game and the second game are different games.

3. The method of claim 1, wherein the first characterization value and the second characterization value each characterize the corresponding game feature in numerical form,

and/or the plurality of game features include a numeric game feature and a non-numeric game feature, wherein a characterization value corresponding to each non-numeric game feature is determined based on a numerically describable attribute value extracted from the non-numeric game feature or based on an encoded value of the non-numeric game feature, the encoded value being obtained by encoding the non-numeric game feature in a unified encoding manner in each game.

4. The method as recited in claim 1, further comprising:

and carrying out normalization processing on the characterization value corresponding to each game feature so as to determine the feature evaluation index of each game feature based on the characterization value after normalization processing.

5. The method of claim 1, wherein the feature evaluation index for each game feature comprises a feature distance determined from a first characterization value and a second characterization value for the game feature.

6. The method of claim 5, wherein the mapping index between the first account number and the second account number is determined by:

Determining characteristic influence coefficients corresponding to the game characteristics respectively;

and determining a mapping index between the first account number and the second account number according to the feature distance of each game feature and the corresponding feature influence coefficient.

7. The method of claim 1, wherein the attribution is used to indicate whether the first account number and the second account number are mapped to the same natural person,

wherein the method further comprises:

if the attribution of the first account and the second account is predicted to be indicative of the same natural person, attribution labels are added to the first account and the second account at the same time, and the attribution labels are used for representing that the two associated accounts are attributed to the same natural person.

8. The method of claim 1, wherein predicting attribution of the first account and the second account based on the determined mapping index comprises:

comparing the mapping index with a preset threshold value;

if the mapping index is not smaller than the preset threshold, the first account and the second account are predicted to be mapped to the same natural person;

if the mapping index is smaller than the preset threshold, the first account and the second account are predicted not to be mapped to the same natural person.

9. The method of claim 8, wherein the preset threshold is determined by:

Acquiring a plurality of training samples, wherein each training sample comprises a test account number and a characterization value of the test account number corresponding to each game feature;

determining a plurality of test mapping indexes based on the characterization values corresponding to the test account numbers;

selecting a plurality of candidate thresholds, and determining account attribution results under each candidate threshold based on the plurality of test mapping indexes;

determining sample prediction evaluation indexes for the plurality of training samples under each candidate threshold based on the determined account attribution result;

and selecting a target candidate threshold from the plurality of candidate thresholds as the preset threshold according to the determined sample prediction evaluation index.

10. The method of claim 9, wherein account attribution results at each candidate threshold are obtained by: and comparing each test mapping index with the candidate threshold value, determining that two accounts corresponding to the test mapping index are not mapped to the same natural person according to the test mapping index smaller than the candidate threshold value, and determining that two accounts corresponding to the test mapping index are mapped to the same natural person according to the test mapping index not smaller than the candidate threshold value.

11. The method of claim 9, wherein determining a sample predictive rating for the plurality of training samples at each candidate threshold based on the determined account assignment result comprises:

for each candidate threshold, determining the precision rate and recall rate corresponding to the training samples under the candidate threshold according to the account attribution result under the candidate threshold;

and determining a sample prediction evaluation index under each candidate threshold according to the precision rate and the recall rate under each candidate threshold.

12. The method of claim 9, wherein the predetermined threshold is a candidate threshold corresponding to a maximum sample predictive evaluation index.

13. An information processing apparatus in a game, the apparatus comprising:

the first numerical value determining module is used for determining a first characterization value of the first account corresponding to each game feature in the plurality of game features in the first game;

the second value determining module is used for determining a second characterization value of the second account corresponding to each game feature in a second game;

the mapping determining module is used for determining a mapping index between the first account number and the second account number based on the characteristic evaluation index of each game characteristic according to the determined first characteristic value and second characteristic value;

And the attribution prediction module predicts attributions of the first account and the second account based on the determined mapping index.

14. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the method of any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, performs the steps of the method according to any of claims 1 to 12.