CN115814432A - Game segment recommendation method, device and storage medium - Google Patents
Game segment recommendation method, device and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of games, and discloses a game segment recommendation method, equipment and a storage medium, wherein the method comprises the following steps: when the game is updated, acquiring user information and game updating information, selecting a target game segment from preset game segments according to the user information and the game updating information, generating the preset game segments based on the game information of a plurality of game players, and pushing the target game segment to the user; according to the invention, when the user updates the game, the game trial playing segment is provided for the user based on the user information and the game updating information, so that the interactivity during game updating can be improved, and the user experience can be further improved.
Description
Technical Field
The present invention relates to the field of game technologies, and in particular, to a method, an apparatus, and a storage medium for recommending game pieces.
Background
At present, a game updating process usually needs to download a large installation package, and the time is different from minutes. In the prior art, video advertisements are usually pushed to users in a waiting process, and the users can only passively accept the video advertisements, so that the user experience is poor.
Disclosure of Invention
The invention mainly aims to provide a game segment recommendation method, equipment and a storage medium, and aims to solve the technical problem that the user experience is poor due to the fact that video advertisements are pushed to the user in the waiting process and the user can only passively accept the video advertisements.
In order to achieve the above object, the present invention provides a game piece recommendation method, including the steps of:
when the game is updated, acquiring user information and game updating information;
selecting a target game segment from preset game segments according to the user information and the game updating information, wherein the preset game segments are generated based on game information of a plurality of game players;
and pushing the target game segment to the user.
Optionally, the step of selecting a target game segment from preset game segments according to the user information and the game update information includes:
determining a favorite game mode and a favorite role type of the user according to the user information;
determining updating waiting time according to the user information and the game updating information;
generating a user label according to at least one of the favorite game mode of the user, the favorite role type of the user and the updating waiting time;
and matching the user tags with the game tags of the preset game segments, and selecting a target game segment from the preset game segments according to a matching result.
Optionally, the step of determining a favorite game mode of the user and a favorite character type of the user according to the user information includes:
determining the times of playing each game mode by the user and the times of winning each game mode by the user according to the user information;
determining a user's favorite game mode based on the number of times the user plays each game mode and the number of times the user wins each game mode;
determining the times of playing each game role by the user and the times of winning the game by using each game role by the user according to the user information;
determining a user's favorite character type based on the number of times the user plays each game character and the number of times the user wins the game using each game character.
Optionally, before the step of acquiring the user information and the game update information when the game is updated, the method further includes:
determining a hot game according to game information of a plurality of game players;
determining a game segment segmentation dimension corresponding to the popular game based on the game type of the popular game;
and segmenting the popular game according to the game segment segmentation dimension to obtain a preset game segment.
Optionally, after the step of segmenting the popular game according to the game segment segmentation dimension to obtain a preset game segment, the method further includes:
acquiring fragment information of the preset game fragment, wherein the fragment information is at least one of a game mode, a role type and a trial playing fragment duration;
and constructing a game label corresponding to the preset game segment based on the segment information.
Optionally, after the step of pushing the target game segment to the user, the method further includes:
when the target game segment is a game segment of a target game, acquiring a trial playing node and/or trial playing duration when the user tries to play the target game segment, wherein the target game is an updating game;
and when the trial playing node and/or the trial playing time meets a preset synchronization condition and the target game is updated, synchronizing the trial playing progress of the user to the target game.
Optionally, after the step of pushing the target game segment to the user, the method further includes:
when the user finishes a preset task in the target game segment, searching resource adjustment information corresponding to the preset task;
and adjusting the resources of the user according to the resource adjustment information.
Optionally, after the step of pushing the target game segment to the user, the method further includes:
when the user plays the target game segment, acquiring a historical playing trial node and/or a historical playing trial duration when the user tries to play the target game segment at the previous time;
and determining the playing content of the target game segment based on the historical playing attempt nodes and/or the historical playing attempt time length.
In addition, to achieve the above object, the present invention further provides a game piece recommendation device, which includes a memory, a processor, and a game piece recommendation program stored on the memory and executable on the processor, wherein the game piece recommendation program is configured to implement the game piece recommendation method as described above.
Further, to achieve the above object, the present invention also provides a storage medium having a game piece recommendation program stored thereon, which when executed by a processor implements the game piece recommendation method as described above.
The invention discloses that when a game is updated, user information and game updating information are acquired, a target game segment is selected from preset game segments according to the user information and the game updating information, the preset game segments are generated based on game information of a plurality of game players, and the target game segment is pushed to a user; according to the invention, when the user updates the game, the game trial playing segment is provided for the user based on the user information and the game updating information, so that the interactivity during game updating can be improved, and the user experience can be further improved.
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FIG. 1 is a schematic diagram of a game piece recommendation device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a game piece recommendation method according to a first embodiment of the present invention;
fig. 3 is a schematic diagram illustrating a trial play prompt message displayed on a display interface of a terminal device according to an embodiment of the game piece recommendation method of the present invention;
FIG. 4 is a flowchart illustrating a game piece recommendation method according to a second embodiment of the present invention;
fig. 5 is a flowchart illustrating a game piece recommendation method according to a third embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a game piece recommendation device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the game piece recommending apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement connection communication among these components. The user interface 1003 may include a Display screen (Display), and the optional user interface 1003 may further include a standard wired interface and a wireless interface, and the wired interface for the user interface 1003 may be a USB interface in the present invention. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the game piece recommender, and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in FIG. 1, memory 1005, identified as one type of computer storage medium, may include an operating system, a network communication module, a user interface module, and a game piece recommender.
In the game piece recommendation device shown in fig. 1, the network interface 1004 is mainly used for connecting with a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting user equipment; the game segment recommendation device calls the game segment recommendation program stored in the memory 1005 through the processor 1001, and executes the game segment recommendation method provided by the embodiment of the present invention.
Based on the hardware structure, the embodiment of the game segment recommendation method is provided.
Referring to fig. 2, fig. 2 is a flowchart illustrating a game piece recommendation method according to a first embodiment of the present invention, and provides the game piece recommendation method according to the first embodiment of the present invention.
In a first embodiment, the game piece recommendation method includes the steps of:
step S10: and when the game is updated, acquiring user information and game updating information.
It should be understood that the executing subject of the method of the embodiment may be a game piece recommending device with data processing, network communication and program running functions, for example, a server or the like, or other electronic devices capable of implementing the same or similar functions, which is not limited by the embodiment.
It is understood that, when a game update is performed, the game being updated may be a conventional game or a cloud game, and in this embodiment and other embodiments, the cloud game is taken as an example for description.
It should be noted that the user information may include a user type, user behavior information, and the like. The user types may include a new user, a general user, and a first play user, among others. Wherein, the new user may be a user without corresponding game behavior information; the first play user may be the user who first plays the game triggering the download of the large resource package. The user behavior information may include: 1. a player unique identifier u; 2. play records of a player the play time of the player is recorded by game dimension
3. For a specific game, the number of times that each type of character of a player plays is counted, r 1 ,r 2 ,r 3 ,r 4 ,r 5 And the number of corresponding wins w 1 ,w 2 ,w 3 ,w 4 ,w 5 }; 4. number of 1V1 games pp in Player Versus Player (PVP) mode 1 3V3 game times pp 2 And 5V5 game times pp 4 And the number ppw of game wins in the corresponding fighting mode of the player 1 ，ppw 2 ，ppw 4 . The PVP mode can be a game mode in which players compete with each other in a game, and is usually an interactive competitive game mode formed by players attacking each other by using game resources; 5. a Player Versus Environment (PVE) game count pe and a Player PVE game win count pew, where the PvE pattern may be a pattern in which players challenge NPC monsters and bosss controlled by a game program in a game.
The game updating information can comprise information such as a game bag body which needs to be updated currently.
Step S20: and selecting a target game segment from preset game segments according to the user information and the game updating information, wherein the preset game segments are generated based on the game information of a plurality of game players.
It should be understood that, the step of selecting the target game segment from the preset game segments according to the user information and the game update information may be that when the user is a new user, there is no corresponding game behavior data, and therefore, the target game segment may be randomly selected from the preset game segments; when the user is a common user, corresponding game behavior data exists, so that the corresponding target game segment can be matched from the preset game segments according to the user information and the game updating information.
In a specific implementation, for example, when a user plays a game for the first time and triggers a large resource package download, the system randomly picks a target game segment from the cloud game video segments of the top 10 hotness.
It is understood that the game information of a plurality of game players may be analyzed, and the preset game segments may be generated according to the analysis result. For example, the segment of the game ranked top 10 from high to low in the cumulative play length of all players during the one week period is taken as the preset game segment.
Step S30: and pushing the target game segment to the user.
It can be understood that, the pushing of the target game segment to the user may be sending a trial game package corresponding to the target game segment to the terminal device corresponding to the user, and after receiving the trial game package, the terminal device displays a trial play prompt message on a display interface of the terminal device.
For ease of understanding, reference is made to fig. 3, but this solution is not described. Fig. 3 is a schematic diagram illustrating that the trial play prompt information is displayed on the display interface of the terminal device, in which the trial play prompt, the update progress bar and the trial play button are displayed in the game update screen, and the user can try to play the target game segment by clicking the trial play button.
In the first embodiment, the method comprises the steps of acquiring user information and game updating information when a game is updated, selecting a target game segment from preset game segments according to the user information and the game updating information, generating the preset game segment based on game information of a plurality of game players, and pushing the target game segment to a user; because this embodiment provides the try-to-play game segment for the user based on user information and game update information when the user carries out the game update to interactivity when the game updates can be improved, and then user experience can be improved.
Further, in order to improve the trial playing experience of the user, after the step S30, the method further includes:
when the target game segment is a game segment of a target game, acquiring a trial playing node and/or trial playing duration when the user tries to play the target game segment, wherein the target game is an updating game;
and when the trial playing node and/or the trial playing time meets a preset synchronization condition and the target game is updated, synchronizing the trial playing progress of the user to the target game.
It should be understood that, in order to improve the trial playing experience of the user, in this embodiment, when the trial playing node and/or the trial playing time length satisfy the preset synchronization condition and the target game is updated, the trial playing progress of the user is synchronized to the target game.
It should be noted that the preset synchronization condition may be preset, for example, the preset condition may be a condition of completing game registration, trying to play the game for 3 minutes, and the like.
In particular implementations, for example, when a user's try-to-play node is registered for completion of a game and the updating of the game being updated is completed, the user's try-to-play progress is synchronized to the updated game. Otherwise, the trial play progress is not synchronized.
Further, in order to increase the trial play enthusiasm of the user, after the step S30, the method further includes:
when the user finishes a preset task in the target game segment, searching resource adjustment information corresponding to the preset task;
and adjusting the resources of the user according to the resource adjustment information.
It can be understood that, in order to improve the trial play enthusiasm of the user, in this embodiment, a preset task may also be set, and when the user completes the task, resource configuration is performed according to resource adjustment information corresponding to the preset task.
It should be noted that the preset task may be preset, for example, the preset task may be to complete a registration procedure. The resource adjustment information corresponding to the preset task can also be preset according to actual requirements, for example, the game downloading speed is correspondingly increased after the registration link is completed, and/or the game resources are rewarded correspondingly after the registration link is completed.
In a specific implementation, for example, when the user completes the registration loop in the target game segment, the user gives priority to resource allocation such as acceleration of downloading of game updates.
Further, in order to ensure the trial play experience of the user, after the step S30, the method further includes:
when the user plays the target game segment, acquiring a historical playing trial node and/or a historical playing trial duration when the user tries to play the target game segment at the previous time;
and determining the playing content of the target game segment based on the historical playing nodes and/or the historical playing duration.
It should be understood that, in order to ensure the trial playing experience of the user, in this embodiment, when the user plays the target game segment, the playing content of the target game segment may also be provided to the user according to the historical trial playing node and/or the historical trial playing duration when the user previously played the target game segment.
In particular implementations, for example, when a user plays a target game segment, the target game segment is played starting from a historical play node at the time the user previously played the target game segment.
Referring to fig. 4, fig. 4 is a flowchart illustrating a game piece recommendation method according to a second embodiment of the present invention, and the game piece recommendation method according to the second embodiment of the present invention is provided based on the first embodiment illustrated in fig. 2.
In the second embodiment, the step S20 includes:
step S201: and determining the favorite game mode and the favorite role type of the user according to the user information.
It should be understood that, in order to improve the accuracy of the selection of the target game segment, in the present embodiment, the target game segment is selected based on the user tag and the try-to-play tag.
It can be understood that determining the user favorite game mode and the user favorite character type according to the user information may be analyzing the user information to obtain the user favorite game mode and the user favorite character type.
Further, in order to improve the accuracy of the user information analysis, the step S201 includes:
determining the times of playing each game mode by the user and the times of winning each game mode by the user according to the user information;
determining a user's favorite game mode based on the number of times the user plays each game mode and the number of times the user wins each game mode;
determining the times of playing each game role by the user and the times of winning the game by using each game role by the user according to the user information;
determining a user's favorite character type based on the number of times the user plays each game character and the number of times the user wins the game using each game character.
It should be understood that, in order to improve the accuracy of the user information analysis, in the present embodiment, the user's favorite game mode is determined according to the number of times the user plays each game mode and the number of times the user wins each game mode, and the user's favorite character type is determined according to the number of times the user plays each game character and the number of times the user wins the game using each game character.
It is to be appreciated that determining the user's favorite game mode based on the number of times the user plays the respective game modes and the number of times the user wins the respective game modes may be generating a game mode value for the respective game mode based on the number of times the user plays the respective game mode and the number of times the user wins the respective game mode, and determining the user's favorite game mode according to the game mode value.
In a specific implementation, the game mode value of the 1V1 mode is taken as an example for description, but the present invention is not limited to this. Game mode value
In the formula, m u A play mode value, pp, of 1V1 mode 1 Number of games played for a user in 1V1 mode, pp 2 Number of games played for a user in 3V3 mode, pp 4 Number of games the user plays in 5V5 mode, pe number of games the user plays in PVE mode, ppw 1 The winning times of the 1V1 mode are won for the user, and the game mode values of other game modes can be obtained in the same way.
It should be understood that determining the user's favorite game mode according to the game mode value may be the game mode having the largest game mode value as the user's favorite game mode.
It is to be understood that determining the user's favorite character type based on the number of times the user plays each game character and the number of times the user wins the game using each game character may be determining a character type value for each character type based on the number of times the user plays each game character and the number of times the user wins the game using each game character, and determining the user's favorite character type according to the character type value.
In the concrete implementation, the description will be given by taking the determination of the character type value of the game character 1 as an example, but the present embodiment is not limited thereto. Role type value
In the formula, r u Is the character type value, r, of game character 1 1 Number of times of playing the game character 1 for the user, r 2 Number of times of playing the game character 2 for the user, r 3 Number of times of playing the game character 3 for the user, r 4 Number of times of playing the game character 4 for the user, r 5 Number of times the user plays the game character 5, w 1 The character type value of the other game character can be obtained similarly for the number of times the user wins the game using the game character 1.
It should be appreciated that determining a user favorite role type based on the role type value can be by taking the role type with the greatest role type value as the user favorite role type.
Step S202: and determining the updating waiting time according to the user information and the game updating information.
It can be understood that the determining of the update waiting time according to the user information and the game update information may be determining a network currently used by the user according to the user information, determining a game bag body currently required to be updated according to the game update information, and determining the update waiting time according to the network currently used by the user and the game bag body currently required to be updated.
In the concrete implementation, if the network currently used by the user is 4G,100Mbit/s and the size of the game bag body needing to be updated is 2G, the update waiting time of the user is calculated to be
Step S203: and generating a user label according to at least one of the favorite game mode of the user, the favorite role type of the user and the updating waiting time.
In a specific implementation, the game mode m is based on the user's favorite game mode u User favorite character type r u And update latency generation user tag { m u ,r u ,t u }。
Step S204: and matching the user tags with the game tags of the preset game segments, and selecting a target game segment from the preset game segments according to a matching result.
It can be understood that, matching the user tag with the game tag of the preset game segment, and selecting the target game segment from the preset game segment according to the matching result may be calculating a set of association degrees between the user tag and the game tag of the preset game segment through a preset association degree formula, and selecting the target game segment from the preset game segment according to the set of association degrees, where the preset association degree formula is as follows:
R＝{i,f(i)},1≤i≤n
wherein R is a bondA set of degrees, f (i) is the degree of association of the user tag with the try-to-play tag, and the user tag is { m } u ,r u ,t u The try-to-play label is { m } i ,r i ,t i V = { V } cloud game segment set 1 ,v 2 ,……v n }。
It should be understood that, the selection of the target game piece from the preset game pieces according to the association degree set may be the selection of a preset game piece corresponding to an association degree infinitely close to 1 from the association degree set as the target game piece.
In a second embodiment, a method for determining a user favorite game mode and a user favorite role type according to user information, determining update waiting time according to the user information and game update information, generating a user tag according to at least one of the user favorite game mode, the user favorite role type and the update waiting time, matching the user tag with a game tag of a preset game segment, and selecting a target game segment from the preset game segment according to a matching result is disclosed; since the target game segment is selected based on the user tag and the trial playing tag, the accuracy of selecting the target game segment can be improved.
Referring to fig. 5, fig. 5 is a flowchart illustrating a game piece recommendation method according to a third embodiment of the present invention, and based on the above embodiments, a game piece recommendation method according to a third embodiment of the present invention is provided.
In the third embodiment, before the step S10, the method further includes:
step S01: a hit game is determined based on game information of a plurality of game players.
It should be understood that, in order to ensure that the preset game segment meets the actual requirement of the user, in this embodiment, the hot game is further segmented according to the game type of the hot game, so as to obtain the preset game segment.
It should be noted that the game information may include information such as a cumulative play time period, a play game name, and the like.
It is to be understood that the determination of the hit game based on the game information of the plurality of game players may be a game ranking top 10 from high to low in the cumulative play length of all players during the one week period as the hit game.
Step S02: and determining the game segment segmentation dimension corresponding to the popular game based on the game type of the popular game.
It should be noted that the game segment splitting dimension may include a game mode, a player selectable character type, a character skill level, a game scene, a game difficulty level, and the like.
It is understood that, the determining of the game segment split dimension corresponding to the popular game based on the game type of the popular game may be looking up the game segment split dimension corresponding to the game type in a preset split table. The preset segmentation table includes a corresponding relationship between the game type and the game segment segmentation dimension, and the corresponding relationship between the game type and the game segment segmentation dimension may be preset, for example, the game segment segmentation dimension corresponding to the MOBA multiplayer competitive game is a game mode, a player-selectable character type, and a character skill level.
Step S03: and segmenting the popular game according to the game segment segmentation dimension to obtain a preset game segment.
In the specific implementation, for the most popular MOBA multi-player competitive game, firstly, the game scene is divided into alpha types according to the game mode, then the optional character types of the players are counted into beta types, and finally the preset number of trial playing segments of the popular game is obtained as alpha beta lambda by combining the hand difficulty gamma types of the characters.
Specifically, taking game XXXX as an example, 1) is divided into a PVP battle mode and a PVE clearance mode according to game modes. The PVP fight mode is divided into 1V1, 3V3 and 5V5 according to the number of players of both fight parties, and 4 game types are obtained together. 2) In the game, the player's optional character types include 5 types of tanks, soldiers, shooters, guests, jurisdictions, assistants, and the like. 3) The skill level of the player character is divided into high, medium and low 3 types. Resulting in 4 x 5 x 3=60 trial play segments.
For the survival competitive game, the slicing method is similar to that of the multiplayer competitive game. Taking game YYYY as an example, 1) is divided into PVEs and PVP according to the game mode. 2) Under the PVP mode, the team formation mode is divided into hundred people for competition and group confrontation (the team members are further subdivided into 2V2, 5V5 and 50V 50) according to the selection of the players, and the PVE mode is added, so that 4 modes are provided. The optional character types of the player in each mode are 5 soldiers, ninja, architects, disarmed persons and survivors, and are divided into 3 minutes, 6 minutes and 10 minutes according to the skill height of the player character to form 4 × 5 × 3=60 trial playing segments. For a live competitive game, a total of 60 trial play segments are generated.
For the game of the creation type of the player, dividing the game scenes into x types according to the game mode, counting the number of the specific creation scenes in the game into y types, and finally obtaining the number of the trial playing segments of the game as xyz by combining the difficulty types of the game.
Taking game 'ZZZZZZ' as an example, 1) is divided into the following 5 types according to the game mode: survival mode, creation mode, adventure mode and spectator mode, 2) combining specific scenes in the game, 13 kinds in total: day and night in the main world, wasteland, soul sand canyon, scarlet forest, tricky forest and basalt delta in the lower bound, the snow world, mountain world, plain, hill, grassland and desert in the last land, 3) the type of difficulty of the combined game: peace, simple, common and difficult, resulting in 5 x 13 x 4=260 trial play pieces.
In a third embodiment, a hot game is determined according to game information of a plurality of game players, a game segment segmentation dimension corresponding to the hot game is determined based on a game type of the hot game, and the hot game is segmented according to the game segment segmentation dimension to obtain a preset game segment; due to the fact that the hot game is segmented based on the game type of the hot game, the preset game segment can meet the actual requirement of the user.
In the third embodiment, after the step S03, the method further includes:
step S04: and acquiring the fragment information of the preset game fragment, wherein the fragment information is at least one of a game mode, a role type and a trial playing fragment duration.
It should be understood that, in order to increase the selection speed of the target game segment, in the embodiment, the trial playing tag corresponding to the preset game segment is pre-constructed, so that the target game segment is selected based on the trial playing tag in the following.
Step S05: and constructing a game label corresponding to the preset game segment based on the segment information.
In the concrete implementation, the most popular MOBA multi-player competitive game in the next time is described in detail. Building a trial playing label corresponding to a preset game segment from 3 dimensions of the game mode, the character type and the length of the trial playing segment: 1) Mode-taking value range set { e, p 1 ,…p n Where e represents a pattern of PVE and p represents a pattern of PVP, { p 1 ,…p n The detailed classifications under the PVP model are respectively. 2) The player-selectable set of character types {1,2, … n }. 3) The length of the trial play session is p minutes.
Specifically, taking game XXXX as an example, 1) is divided into a PVP battle mode and a PVE clearance mode according to game modes. The PVP fight mode is divided into 1V1, 3V3 and 5V5 according to the number of players of both fight parties, and the value range set of the mode is recorded {1,2 1 ,2 3 ,2 5 In which 1 represents a pattern of PVE,2 represents a pattern of PVP, {2 1 ,2 3 ,2 5 1V1, 3V3 and 5V5 under PVP model respectively. 2) The character types selectable by the player comprise 5 types of tanks, soldiers, shooters, stabs, jurisdictions, assistants and the like, and the value range set is defined to be {1,2,3,4,5} according to different character types. 3) Each segment is divided into 3 minutes, 6 minutes and 10 minutes of 3 grades according to the skill level of the player character, and the value is defined according to the actual time length of the segment. 4) And according to the value range set defined above, marking corresponding label values for each trial playing segment according to three dimensions of a game mode, a role type and a trial playing segment duration. For example, if a character A with a middle skill level is playing a game clip video of about 5.5 minutes in a 5V5 battle, and the character A belongs to a tank hero with a value of 1, the corresponding trial playing label is {2 } 5 ，1,5.5}。
In a third embodiment, the method includes acquiring segment information of the preset game segment, wherein the segment information is at least one of a game mode, a role type and a trial playing segment duration, and constructing a game tag corresponding to the preset game segment based on the segment information; because the trial playing labels corresponding to the preset game segments are constructed in advance, the target game segments can be conveniently selected based on the trial playing labels subsequently, and the selection speed of the target game segments can be increased.
In addition, an embodiment of the present invention further provides a storage medium, where a game piece recommendation program is stored on the storage medium, and when executed by a processor, the game piece recommendation program implements the game piece recommendation method as described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method of the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but in many cases, the former is a better implementation. Based on such understanding, the technical solutions of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g., a Read Only Memory (ROM)/Random Access Memory (RAM), a magnetic disk, an optical disk), and includes several instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A game segment recommendation method is characterized by comprising the following steps:
when the game is updated, acquiring user information and game updating information;
selecting a target game segment from preset game segments according to the user information and the game updating information, wherein the preset game segments are generated based on game information of a plurality of game players;
and pushing the target game segment to the user.
2. The game segment recommendation method of claim 1, wherein the step of selecting a target game segment from preset game segments according to the user information and the game update information comprises:
determining a favorite game mode and a favorite role type of the user according to the user information;
determining updating waiting time according to the user information and the game updating information;
generating a user label according to at least one of the favorite game mode of the user, the favorite role type of the user and the updating waiting time;
and matching the user tags with the game tags of the preset game segments, and selecting a target game segment from the preset game segments according to a matching result.
3. The game piece recommendation method of claim 2, wherein the step of determining the user's favorite game mode and the user's favorite character type based on the user information comprises:
determining the times of playing each game mode by the user and the times of winning each game mode by the user according to the user information;
determining a user's favorite game mode based on the number of times the user plays each game mode and the number of times the user wins each game mode;
determining the times of playing each game role by the user and the times of winning the game by using each game role by the user according to the user information;
determining a user's favorite character type based on the number of times the user plays each game character and the number of times the user wins the game using each game character.
4. The game piece recommendation method according to any one of claims 1 to 3, wherein the step of acquiring the user information and the game update information at the time of game update further comprises:
determining a hot game according to game information of a plurality of game players;
determining a game segment segmentation dimension corresponding to the popular game based on the game type of the popular game;
and segmenting the popular game according to the game segment segmentation dimension to obtain a preset game segment.
5. The game segment recommendation method of claim 4, wherein after the step of segmenting the popular game according to the game segment segmentation dimension to obtain the preset game segment, the method further comprises:
acquiring fragment information of the preset game fragment, wherein the fragment information is at least one of a game mode, a role type and a trial playing fragment duration;
and constructing a game label corresponding to the preset game segment based on the segment information.
6. The game piece recommendation method according to any one of claims 1 to 3, wherein after the step of pushing the target game piece to the user, further comprising:
when the target game segment is a game segment of a target game, acquiring a trial playing node and/or trial playing duration when the user tries to play the target game segment, wherein the target game is an updating game;
and when the trial playing node and/or the trial playing time meets a preset synchronization condition and the target game is updated, synchronizing the trial playing progress of the user to the target game.
7. The game piece recommendation method of any one of claims 1 to 3, wherein after the step of pushing the target game piece to the user, further comprising:
when the user finishes a preset task in the target game segment, searching resource adjustment information corresponding to the preset task;
and adjusting the resources of the user according to the resource adjustment information.
8. The game piece recommendation method of any one of claims 1 to 3, wherein after the step of pushing the target game piece to the user, further comprising:
when the user plays the target game segment, acquiring a historical playing trial node and/or a historical playing trial duration when the user tries to play the target game segment at the previous time;
and determining the playing content of the target game segment based on the historical playing nodes and/or the historical playing duration.
9. A game segment recommendation device characterized by comprising: a memory, a processor and a game piece recommender stored on the memory and executable on the processor, the game piece recommender when executed by the processor implementing the game piece recommendation method as claimed in any one of claims 1 to 8.
10. A storage medium characterized in that a game segment recommendation program is stored thereon, which when executed by a processor implements a game segment recommendation method according to any one of claims 1 to 8.
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