CN107741898B - Game player operation preference analysis method and system based on big data - Google Patents
Game player operation preference analysis method and system based on big data Download PDFInfo
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Abstract
The invention provides a game player operation preference analysis system and method based on big data. According to the method, the big data acquisition and analysis of the user operation input content and the operation action process are associated with the specific game scene when the user executes the operations, the operation chain is formed aiming at the front and back operations under the specific game scene, the operation chain and the associated specific environment data are used as the object of big data analysis, the big data analysis algorithms such as clustering and the like are applied, the big data analysis of the user preference in the specific game environment is realized, the generated analysis conclusion can be used for GUI interface optimization or player assistance, the adaptability of the analysis conclusion to the specific game environment is strong, and the method has sufficient scene pertinence.
Description
Technical Field
The invention relates to the technical field of big data application, in particular to a method and a system for analyzing operation preference of a game player based on big data.
Background
Currently, the entire human society has rapidly entered the big data era. In particular, various computers or intelligent devices are used as carriers, and user data acquisition, uploading and analysis functions which need to be authorized are built in an operating system, an application program and network service. The method comprises the steps of collecting massive, various and real-time user data to form an ultra-large-scale data set, and obtaining valuable information such as user preference and action rules behind the data by using a big data analysis method. Based on the information obtained by the big data analysis, the content preferentially provided to the user can be screened, the flow for providing the service to the user can be optimized, and the like.
Among networked game devices and services, relevant operators are actively applying big data technology to achieve the purposes of improving user experience and adding value to game services. For example, chinese patent document CN106878409 discloses a game data processing system and a processing method, including a data acquisition module, where the data acquisition module includes an API data acquisition module and an acquisition and analysis module; the data storage module is electrically connected with the data acquisition module; and the data analysis module is electrically connected with the data storage module and is used for carrying out statistical analysis on the API data and the game process parameters and generating an analysis result. And instructive data are obtained through statistical analysis, so that the player can understand and analyze the game, and the competitive level of the player is improved. The prior art focuses on acquiring data generated by a user in a game process, and can analyze video data of game videos besides processing and collecting official API data, so that more source data can be collected. For another example, chinese patent document CN107050863A discloses a game auxiliary manipulation method and system based on big data analysis, which can send the manipulation data of the second player matching with the game type and the operation terminal of the first player to the first player, so as to assist the first player and achieve the matching of game fun and game difficulty. Chinese patent document CN106648397 discloses a method and a system for processing game operation records of a mobile terminal, in which interface operations of a game player are recorded, operation data are collected, a script file is exported, the file is processed, and gesture operations, trigger time and corresponding screen coordinates during the interface operations of the player are obtained; presenting points corresponding to screen coordinates corresponding to the gesture operation in a visual view form, such as a thermodynamic diagram, a scatter diagram and a histogram; the visual view obtained by the method can help analyze the operation intensity and the operation load of the user, so that assistance is provided for researching the design of the game UI, for example, whether the game UI design conforms to the operation habit of the user is analyzed.
Therefore, the big data acquisition and analysis are applied to the prior art of game products, and are based on the operation data of players in the game interaction process, and the acquisition mode comprises interface acquisition and extraction from game video pictures; furthermore, rules contained in the operation data are statistically analyzed, and then guiding operation suggestions are provided for the player, or suggestions for adjusting interface arrangement and display are fed back to the designer of the game operation interface.
The defects in the prior art include: first, the operation data collected through the interface and extracted through the screen in the prior art generally represents the operation input content (for example, the selection of menu items in the game) and the operation action process (for example, the position and frequency of the click action, the length and range of the sliding action in the touch game, etc.) of the player, and further, the habit and preference of the player expressed in the operation data can be analyzed; however, any operation of a player in a game is performed in a specific game environment, which refers to a state of an object (e.g., a character representing the player in the game) for which the player takes an operation and a correlation between the object and other objects in the game while operating; in the prior art, specific game environment data corresponding to operation is not collected in a targeted manner, and the operation data of a player and the specific game environment data during operation are not correlated to carry out big data analysis, so that a generated analysis result (such as guidance to the player) is not applicable easily. Secondly, during the game, the previous and next operations of the player are often a set of operations linked with each other, the input or action of the previous operation determines or affects several subsequent operations, and the prior art does not analyze big data of the previous and next operations which are related to the player as a whole. Thirdly, in the aspect of optimizing the game interactive interface, the prior art considers the distribution rules and preferences of the players in the operation actions in the statistical analysis, and optimizes the interactive interface, but the relationship between the rules and preferences of the players in the operation actions and the specific game environment is not fully considered, which easily causes the limited application occasions of the optimized interactive interface, and the effect of improving the operation experience is not ideal.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a game player operation preference analysis method and system based on big data. The method collects the operation data of a player and the specific game environment data associated with the operation data from the game application or service running on the networked intelligent equipment, and connects the collected operation data of a plurality of times before and after as an operation chain according to the correlation degree between the operation before and after; aggregating big data by using an operation chain as a basic unit, and developing player operation preference analysis facing the big data; and optimizing a Graphical User Interaction (GUI) interface of the game or providing services such as operation assistance for the player and the like by taking the player preference analysis result as a basis factor.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme:
a big-data-based game player operation preference analysis system, comprising: the system comprises an operation data acquisition layer, an operation data storage layer, an operation data analysis processing layer and an application layer;
the operation data acquisition layer is used for establishing connection with the intelligent equipment through a network, and acquiring operation data of a player and specific game environment data associated with the operation data in real time from game applications or services running on the intelligent equipment;
the operation data storage layer obtains operation data and specific game environment data associated with the operation data, and integrates the operation data with dispersed sources and the specific game environment data provided by the operation data acquisition layer into a structured data storage file taking a time interval as a unit by taking a time axis as a clue through a time axis structured storage mechanism;
the operation data analysis processing layer obtains a structured data storage file from the operation data storage layer, extracts operation data, determines specific game environment data associated with the operation data, and connects the operation data of a plurality of times before and after and the specific game environment data thereof into an operation chain according to the correlation degree between the operations before and after; aggregating big data by using an operation chain as a basic unit, and developing player operation preference analysis facing the big data;
the application layer obtains big data analysis results of player preference attributes associated with a specific game environment from the operational data analysis processing layer and executes various functional applications based on the results.
Preferably, the operational data acquisition layer specifically comprises: the system comprises a log file interface, an operation interface, a game scene interface, a real-time service flow interface and a data normalization unit; the log file interface obtains a log recording player operation input content and input time thereof from a game application or service in real time; the operation interface periodically samples a cursor clicking position coordinate of a player on a Graphical User Interaction (GUI) interface of a game or a touch position coordinate in a touch game, and records the position coordinate and sampling time as operation action process data; the game scene interface is used for periodically sampling all objects existing in a specific game scene presented on a Graphical User Interaction (GUI) interface when a player operates, and reading an object list; the real-time traffic interface periodically queries and samples the state data of each object for all objects involved in a particular game scene presented during user operation.
Preferably, the operation data analysis processing layer specifically includes: the device comprises an environment mode analysis unit, an operation environment association unit, an operation chain big data generation unit and a big data preference analysis unit; the environment mode analysis unit extracts an object list and an object state contained in each specific game scene from each structured data storage file, and marks an environment mark on each specific game scene according to the difference degree of the object list and the object state, wherein scenes with the same game environment are marked with the same environment mark; the operation environment association unit extracts recorded operation data from the structured data storage file, wherein the operation data comprises operation input content data and operation action process data, maps the operation data to specific game scenes at the same acquisition time point according to the occurrence time of operation input or the acquisition time of operation action, and determines specific game environment data associated with the operation data according to the environment mark marked on each specific game scene; the operation environment association unit is also used for integrating all operation data associated to the same specific game environment by a single player, including operation input content data and operation action process data, into an operation chain according to the time sequence of operation; the operation environment association unit uploads the operation chain data and the associated specific game environment data to the operation chain big data generation unit; the operation chain big data generating unit aggregates operation chain data uploaded by all players and associated specific game environment data, and stores the operation chain data and the associated specific game environment data in a structured data file form to form operation chain big data; the big data preference analysis unit analyzes the operation chain big data aggregated by the operation chain big data generation unit through a big data analysis algorithm, and obtains the operation preference of the user under the specific game environment data.
It is further preferable that, for any two adjacent screens of specific game scenes, the environment pattern analysis unit first determines whether a percentage of identical objects contained in the two adjacent screens of specific game scenes to all objects in each screen of scene is lower than a threshold, and determines that the two screens of specific game scenes have different game environments if the percentage of at least one screen of scene in the two screens of scenes is lower than the threshold; if the percentage of the same objects in all the objects contained in two adjacent scenes of the specific game is greater than or equal to the threshold value, then calculating the overall state difference degree of all the same objects in the two scenes by using the object state values; and if the overall state difference degree is greater than or equal to the threshold value, the two specific game scenes are judged to have different game environments, and if the overall state difference degree is lower than the threshold value, the two specific game scenes are judged to have the same game environment.
Preferably, the application layer is used for implementing a player assistance function, and outputting necessary prompts to the assisted player according to the specific game environment of the assisted player based on the player operation preference under the specific game environment provided by the operation data analysis and processing layer; or the application layer is used for realizing a Graphical User Interaction (GUI) interface of the optimized game, and optimizing interface options and button positions in the specific game environment according to the operation input preference and the operation action preference of the player in the specific game environment.
The invention further provides a game player operation preference analysis method based on big data, which is characterized by comprising the following steps:
establishing connection with intelligent equipment through a network, and collecting operation data of a player and specific game environment data associated with the operation data in real time from game applications or services running on the intelligent equipment;
obtaining operation data and specific game environment data associated with the operation data, and integrating the operation data and the specific game environment data which are scattered by sources into a structured data storage file which takes a time interval as a unit by taking a time axis as a clue by adopting a time axis structured storage mechanism;
obtaining a structured data storage file, extracting operation data, determining specific game environment data associated with the operation data, and connecting the operation data of a plurality of times before and after and the specific game environment data thereof into an operation chain according to the correlation degree between the operation before and after; aggregating big data by using an operation chain as a basic unit, and developing player operation preference analysis facing the big data;
big data analysis results of player preference attributes associated with a particular gaming environment are obtained, and various functional applications are executed based on the results.
Preferably, the player's operational data and the specific game environment data associated with the operational data are collected in any one or more of the following ways: obtaining a log recording player operation input content and input time thereof from a game application or service in real time; sampling the coordinate of a cursor clicking position of a player on a Graphical User Interaction (GUI) interface of a game at regular time, or touching the position coordinate in a touch game, and recording the position coordinate and sampling time as the operation action process data; the method comprises the steps of sampling all objects existing in a specific game scene presented on a Graphical User Interaction (GUI) interface when a player operates in a timing mode, reading an object list, and inquiring and sampling state data of each object in a timing mode aiming at all objects involved in the specific game scene presented when the player operates.
Preferably, the specific game environment data associated with the operation data is determined by: extracting an object list and an object state contained in each specific game scene from each structured data storage file, labeling an environment mark for each specific game scene according to the difference degree of the object list and the object state, and labeling the same environment mark for scenes with the same game environment; and extracting recorded operation data from the structured data storage file, wherein the operation data comprises operation input content data and operation action process data, mapping the operation data to specific game scenes at the same acquisition time point according to the occurrence time of the operation input or the acquisition time of the operation action, and determining specific game environment data associated with the operation data according to the environment mark marked on each specific game scene.
It is further preferred that the degree of difference between the object list and the object state between the specific game scenes is judged as follows: judging whether the percentage of the same objects contained in two adjacent screens of specific game scenes in all the objects in each screen scene is lower than a threshold value or not, and if the percentage of at least one screen scene in the two screens of specific game scenes is lower than the threshold value, judging that the two screens of specific game scenes have different game environments; if the percentage of the same objects in all the objects contained in two adjacent scenes of the specific game is greater than or equal to the threshold value, then calculating the overall state difference degree of all the same objects in the two scenes by using the object state values; and if the overall state difference degree is greater than or equal to the threshold value, the two specific game scenes are judged to have different game environments, and if the overall state difference degree is lower than the threshold value, the two specific game scenes are judged to have the same game environment.
Preferably, the functional applications executed based on the results of the big data analysis of the player preference attributes associated with the particular gaming environment include: the player assistance function is realized, and necessary prompts are output to the assisted player according to the specific game environment of the assisted player and based on the player operation preference under the specific game environment provided by the operation data analysis and processing layer; or, a Graphical User Interaction (GUI) interface for implementing an optimized game optimizes interface options and button positions given to a specific game environment according to operational input preferences and operational action preferences of a player in the specific game environment.
(III) advantageous effects
Compared with the prior art, the invention provides a game player operation preference analysis system and method based on big data, which has the following beneficial effects:
according to the method, the big data acquisition and analysis of the user operation input content and the operation action process are associated with the specific game scene when the user executes the operations, the operation chain is formed aiming at the front and back operations under the specific game scene, the operation chain and the associated specific environment data are used as the object of big data analysis, the big data analysis algorithms such as clustering and the like are applied, the big data analysis of the user preference in the specific game environment is realized, the generated analysis conclusion can be used for GUI interface optimization or player assistance, the adaptability of the analysis conclusion to the specific game environment is strong, and the method has sufficient scene pertinence.
Drawings
FIG. 1 is a schematic diagram of an overall structure of a big data-based game player operation preference analysis system according to the present invention;
FIG. 2 is a schematic view of the operational data acquisition layer structure of the system of the present invention;
FIG. 3 is a schematic diagram of a time-axis structured storage mechanism adopted by the present invention;
FIG. 4 is a schematic diagram of the operating data analysis processing layer of the system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic diagram of an overall structure of a big data-based game player operation preference analysis system according to the present invention. The system is integrally divided into an operation data acquisition layer, an operation data storage layer, an operation data analysis processing layer and an application layer.
The operation data acquisition layer is used for establishing connection with the intelligent device through a network, and acquiring operation data of a player and specific game environment data associated with the operation data in real time from game applications or services running on the intelligent device. The operational data of the player generally includes: data indicating the operation input content (for example, selection of a menu item in the game, selection of a direction key of a movement target in the game, selection of an instruction key for operating a character in the game) and the operation action process (for example, the position and frequency of a click action, the length and range of a slide action in the touch game, and the like) of the player. The specific game environment data refers to the state (e.g., position coordinates of the object in the game space, the own attribute of the object) of each object (e.g., a character representing a player in the game, a character representing another player, an item, a pipe card obstacle, a bonus, etc.) in the game scene for which the player takes action, and the mutual relationship of the objects at the time of operation.
As shown in fig. 2, the operational data acquisition layer specifically includes: the system comprises a log file interface, an operation interface, a game scene interface, a real-time service flow interface and a data normalization unit. The log file interface obtains a log recording player operation input content and input time thereof from a game application or service in real time; a Hook (Hook) plug-in may be embedded in the game application or service, and the operation input contents generated by each operation of the player and the input time thereof are recorded in the player log in real time. The method comprises the steps that an operation interface samples cursor clicking position coordinates of a player on a Graphical User Interaction (GUI) interface of a game at regular time, or touch position coordinates in a touch game, and records the position coordinates and sampling time as operation action process data; the intelligent devices are provided with a user input coordinate interface matched with a Graphical User Interaction (GUI) interface, and position coordinates of each cursor click of a user or touch position coordinates are provided for the GUI interface; the plug-in of the game application or service can collect the coordinate value provided by the user input coordinate interface and transmit the coordinate value to the operation interface. The game scene interface is used for determining all objects existing in a game scene presented on a Graphical User Interaction (GUI) interface when the player operates, wherein the objects comprise objects for which the player takes operation and other objects in the game; the generation of the game picture adopts an object modeling method, namely, on the basis of an original object model, values are assigned to various parameter domains of the model according to the state of the current game, the display effect of the original object model is updated according to the assigned parameters, an object displayed in a certain screen specific game scene is formed, all objects (background elements of the scene and the like are generally defined as objects) related to the screen specific game scene are combined in sequence, and the game scene presented on a Graphical User Interaction (GUI) interface is formed; the game scene interface obtains configuration parameters defining a specific game scene through timing sampling, and reads an object list in the configuration parameters to obtain all objects existing in the game scene presented on a Graphical User Interaction (GUI) interface. The real-time service flow interface periodically inquires and samples state data of each object aiming at all objects related in a specific game scene presented during user operation; for example, for a networked game, the state data of each object is stored in the real-time configuration file of the game server, and the state data is updated according to the instructions and parameters of the service data stream bidirectionally interacted between the game server and the intelligent device, so that the real-time service stream interface can monitor the service data stream, and further obtain the state data of each object. The data normalization unit is connected with the log file interface, the operation interface, the game scene interface and the real-time service flow interface; aiming at scattered operation input content data, operation action process data, game scene object list data and object state data of multiple format types provided by the interface, the data normalization unit encapsulates the data into event packets of a uniform format, the event packets are cached in a first-in first-out cache region, and a data stream formed by the event packets is sent to an operation data storage layer; and when an instruction that the received event packet is fed back by the data storage layer is received, deleting the event packet in the cache region and recycling the cache space.
The operation data storage layer extracts the event package from the data stream sent by the data normalization unit, and obtains operation input content data, operation action process data, game scene object list data and object state data. The operation data storage layer adopts a specially designed time axis structured storage mechanism, as shown in fig. 3, the time axis is divided into time unit intervals according to a predetermined unit length, for example, each time unit is 10s, 50 time units form a time unit interval, and a structured data storage file is set for each time unit interval; the time unit section to which the operation input content data, the operation action process data, the game scene object list data, and the object state data belong is determined based on the occurrence or collection time of the operation input content data, the operation action process data, the game scene object list data, and the object state data (for example, the input time of the operation input content recorded in the player log, the occurrence time of the player click or touch action, the arrangement time of the specific game scene and the game object state, and the like), and these data are filled in the structured data storage file corresponding to the time unit section. The operation data storage layer changes the general way that the existing big data system stores data according to structured and unstructured distinguishing, integrates operation data with scattered sources provided by the operation data acquisition layer into a structured data storage file with a time interval as a unit by taking a time axis as a clue, and lays a foundation for the mutual correlation among data and the integration of an operation chain.
The operation data analysis processing layer obtains a structured data storage file from the operation data storage layer, extracts operation data, determines specific game environment data associated with the operation data, and connects the operation data of a plurality of times before and after and the specific game environment data thereof into an operation chain according to the correlation degree between the operations before and after; and aggregating big data on the basis of the operation chain unit, and developing player operation preference analysis facing the big data. As shown in fig. 4, the operation data analysis processing layer specifically includes: the device comprises an environment mode analysis unit, an operation environment association unit, an operation chain big data generation unit and a big data preference analysis unit.
The environment mode analysis unit extracts an object list and an object state contained in each specific game scene sampled on each time unit of each time unit interval from the structured data storage file of each time unit interval. For any two adjacent specific game scenes, firstly judging whether the percentage of the same objects contained in the two adjacent specific game scenes in all the objects in each scene is lower than a threshold value, and if the percentage of at least one scene in the two scenes is lower than the threshold value, judging that the two specific game scenes have different game environments; if the percentage of the same objects in all the objects contained in two adjacent scenes of the specific game is greater than or equal to the threshold value, then calculating the overall state difference degree of all the same objects in the two scenes by using the object state values; and if the overall state difference degree is greater than or equal to the threshold value, the two specific game scenes are judged to have different game environments, and if the overall state difference degree is lower than the threshold value, the two specific game scenes are judged to have the same game environment. According to the judgment result, the environment pattern analysis unit marks an environment mark on each specific game scene, and scenes with the same game environment are marked with the same environment mark.
For example, in a structured data storage file, a particular game scene S is sampled every time unit (every 10S)1，S2......Sn-1，Sn......SmIn which two adjacent scenes Sn-1，SnMiddle, scene Sn-1All objects contained are grouped as Objectn-1＝{O1，O2......On-1，On......Ok}, scene SnAll objects contained are grouped as Objectn＝{O′1，O′2......O′l-1，O′l......O′mDetermine two scenes Sn-1，SnThe same object contained in the above two sets is the intersection of the above two sets
Judging the intersection Objectn-1∩ ObjectnRespectively account for the Object number of the set Objectn-1And aggregate ObjectnA percentage of the number of objects, and if any one of the percentages is below a threshold, determining that the two particular game scenes have different game environments. If both percentages are greater than or equal to the threshold, it indicates two adjacent scenes Sn-1，SnThe objects in (1) are generally seen to be similar, and then the intersection is aimed at
Each object in the set of objects, analyzing the object in the scene Sn-1State value in (1) and S in scenenThe absolute difference of the state values of (2), and thus for the intersection Objectn-1∩ObjectnThe absolute difference values of the state values of all the objects are weighted and summed as the overall difference degree of the states, namely
The operation environment association unit extracts recorded operation data from a structured data storage file of a time unit interval, wherein the operation data comprises operation input content data and operation action process data, maps the operation data to specific game scenes at the same acquisition time point according to the occurrence time of the operation input or the acquisition time of the operation action, and determines the specific game environment data associated with the operation data according to the environment mark marked on each specific game scene. The specific game environment data represents the state (e.g., position coordinates of the object in the game space, self of the object) of each object in the game scene (e.g., a character representing a player in the game, characters representing other players, props, pipe card obstacles, bonus items, etc.) for which the player takes actionBody attributes) and the interrelationship of objects while operating. For a plurality of specific game scenes labeled with the same environmental label, a set of the same objects in the specific game scenes, such as the intersecting Object mentioned above, is determinedn-1∩ ObjectnRepresenting two scenes Sn-1，SnThe state values of the objects in the same object set in each scene with the same environmental label are obtained, the average state value of the state values is obtained as the specific game environment data of the scenes with the same environmental label, and the specific game environment data is associated with the operation data corresponding to the scenes.
Further, the operation environment associating means integrates all operation data associated with the same specific game environment by a single player, including operation input content data and operation action process data, into an operation chain in accordance with the time sequence of operations. The operation chain reflects the whole of a series of operation inputs and actions of the player before and after the player in a specific game environment. And, the operation environment associating unit uploads the operation chain data and the associated specific game environment data to the operation chain big data generating unit. The operation chain big data generation unit aggregates operation chain data uploaded by all players and associated specific game environment data, and stores the operation chain data and the associated specific game environment data in a structured data file form to form operation chain big data.
The big data preference analysis unit analyzes the operation chain big data aggregated by the operation chain big data generation unit through a big data analysis algorithm, and obtains the operation preference of the user under the specific game environment data.
Specifically, the big data preference analysis unit applies an automatic clustering algorithm based on records of big data of operation chains of all players to automatically classify the big data of the operation chains into a plurality of operation preference clusters. The big data preference analysis unit extracts all operation chain data of all players, and the total number of the operation chains is assumed to be n, and the operation chain data is counted as
Presetting to classify the operation chain data into k preference clusters, then randomly selecting k values from n operation chains as initial cluster centers, and counting as Ec1，Ec2，......，Eck(ii) a Calculation of Ei-n，Ei-n+1...，EiEach operation chain data (including operation data and specific game environment data associated therewith) and Ec1，Ec2，......，EckThe distance value V of each cluster centeri-Ck＝|Ei-EckI, and then Ei-n，Ei-n+1...，EiEach operation chain in (1) is assigned to Ec1，Ec2，......，EckThe cluster to which the cluster center closest to the cluster center belongs; then, recalculating the clustering center of each cluster; then calculate Ei-n，Ei-n+1...，EiAnd E is calculated according to the distance value of each operation chain and the recalculated cluster centeri-n，Ei-n+1...，EiEach operation chain in the operation chain is reassigned to the cluster to which the cluster center closest to the operation chain belongs; then updating the clustering center again; and iterating the processes until the cluster center is not changed after updating. Furthermore, for each cluster of operation chain data, the incidence rate of each type of operation input and operation action is counted, and the operation input and operation action with the highest incidence rate are used as the preference attributes of the players in the specific game environment.
The application layer obtains big data analysis results of player preference attributes associated with a specific game environment from the operation data analysis processing layer, and executes various functional applications based on the results. For example, for the player assist function, according to the specific game environment of the assisted player, the operation input preferred by the player in the specific game environment can be determined according to the conclusion of the cluster analysis, and necessary prompt is given to the current assisted player. Or, for a Graphical User Interaction (GUI) interface of the optimized game, according to the operation input preference and the operation action preference of the player in a specific game environment, the method of setting or highlighting the preferred input option, and placing the preferred button in a block with frequent operation action in the interface can be adopted to optimize the human-computer interaction interface of the game.
According to the method, the big data acquisition and analysis of the user operation input content and the operation action process are associated with the specific game scene when the user executes the operations, the operation chain is formed aiming at the front and back operations under the specific game scene, the operation chain and the associated specific environment data are used as the object of big data analysis, the big data analysis algorithms such as clustering and the like are applied, the big data analysis of the user preference in the specific game environment is realized, the generated analysis conclusion can be used for GUI interface optimization or player assistance, the adaptability of the analysis conclusion to the specific game environment is strong, and the method has sufficient scene pertinence.
It is to be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A big-data-based game player operation preference analysis system, comprising: the system comprises an operation data acquisition layer, an operation data storage layer, an operation data analysis processing layer and an application layer;
the operation data acquisition layer is used for establishing connection with the intelligent equipment through a network, and acquiring operation data of a player and specific game environment data associated with the operation data in real time from game applications or services running on the intelligent equipment;
the operation data storage layer obtains operation data and specific game environment data associated with the operation data, and integrates the operation data with dispersed sources and the specific game environment data provided by the operation data acquisition layer into a structured data storage file taking a time interval as a unit by taking a time axis as a clue through a time axis structured storage mechanism;
the operation data analysis processing layer obtains a structured data storage file from the operation data storage layer, extracts operation data, determines specific game environment data associated with the operation data, and connects the operation data of a plurality of times before and after and the specific game environment data thereof into an operation chain according to the correlation degree between the operations before and after; aggregating big data by using an operation chain as a basic unit, and developing player operation preference analysis facing the big data;
the application layer obtains a big data analysis result of a player preference attribute associated with a specific game environment from the operation data analysis processing layer, and executes various functional applications based on the result;
the operational data acquisition layer specifically comprises: the system comprises a log file interface, an operation interface, a game scene interface, a real-time service flow interface and a data normalization unit; the log file interface obtains a log recording player operation input content and input time thereof from a game application or service in real time; the operation interface periodically samples a cursor clicking position coordinate of a player on a Graphical User Interaction (GUI) interface of a game or a touch position coordinate in a touch game, and records the position coordinate and sampling time as operation action process data; the game scene interface is used for periodically sampling all objects existing in a specific game scene presented on a Graphical User Interaction (GUI) interface when a player operates, and reading an object list; the real-time service flow interface periodically inquires and samples state data of each object aiming at all objects related in a specific game scene presented during user operation;
the intelligent device is provided with a user input coordinate interface matched with a Graphical User Interaction (GUI) interface, and position coordinates of each cursor click of a user or touch position coordinates are provided for the GUI interface; the plug-in of the game application or service can collect the coordinate value provided by the user input coordinate interface and transmit the coordinate value to the operation interface;
the operation data analysis processing layer specifically comprises: the device comprises an environment mode analysis unit, an operation environment association unit, an operation chain big data generation unit and a big data preference analysis unit; the environment mode analysis unit extracts an object list and an object state contained in each specific game scene from each structured data storage file, and marks an environment mark on each specific game scene according to the difference degree of the object list and the object state, wherein scenes with the same game environment are marked with the same environment mark; the operation environment association unit extracts recorded operation data from the structured data storage file, wherein the operation data comprises operation input content data and operation action process data, maps the operation data to specific game scenes at the same acquisition time point according to the occurrence time of operation input or the acquisition time of operation action, and determines specific game environment data associated with the operation data according to the environment mark marked on each specific game scene; the operation environment association unit is also used for associating all operation data of a single player to the same specific game environment, including operation input content data and operation action process data, and connecting the operation data and the specific game environment data thereof into an operation chain according to the correlation degree between front and back operations; the operation environment association unit uploads the operation chain data and the associated specific game environment data to the operation chain big data generation unit; the operation chain big data generating unit aggregates operation chain data uploaded by all players and associated specific game environment data, and stores the operation chain data and the associated specific game environment data in a structured data file form to form operation chain big data; the big data preference analysis unit analyzes the operation chain big data aggregated by the operation chain big data generation unit through a big data analysis algorithm, and obtains the operation preference of the user under the specific game environment data.
2. The big-data based game player operation preference analysis system according to claim 1, wherein the environment pattern analysis unit first determines whether a percentage of identical objects contained in two adjacent screens of the specific game scenes to all objects in each screen of the specific game scenes is lower than a threshold value, and determines that the two screens of the specific game scenes have different game environments if the percentage of at least one screen of the two screens of the specific game scenes is lower than the threshold value; if the percentage of the same objects in all the objects contained in two adjacent scenes of the specific game is greater than or equal to the threshold value, then calculating the overall state difference degree of all the same objects in the two scenes by using the object state values; and if the overall state difference degree is greater than or equal to the threshold value, the two specific game scenes are judged to have different game environments, and if the overall state difference degree is lower than the threshold value, the two specific game scenes are judged to have the same game environment.
3. The big-data based game player operation preference analysis system according to claim 2, wherein the application layer is configured to implement a player assistance function for outputting necessary prompts to the assisted player based on the player operation preference under the specific game environment provided by the operation data analysis processing layer according to the specific game environment of the assisted player; or the application layer is used for realizing a Graphical User Interaction (GUI) interface of the optimized game, and optimizing interface options and button positions in the specific game environment according to the operation input preference and the operation action preference of the player in the specific game environment.
4. A big data-based game player operation preference analysis method is characterized by comprising the following steps:
establishing connection with intelligent equipment through a network, and collecting operation data of a player and specific game environment data associated with the operation data in real time from game applications or services running on the intelligent equipment;
obtaining operation data and specific game environment data associated with the operation data, and integrating the operation data and the specific game environment data which are scattered by sources into a structured data storage file which takes a time interval as a unit by taking a time axis as a clue by adopting a time axis structured storage mechanism;
obtaining a structured data storage file, extracting operation data, determining specific game environment data associated with the operation data, and connecting the operation data of a plurality of times before and after and the specific game environment data thereof into an operation chain according to the correlation degree between the operation before and after; aggregating big data by using an operation chain as a basic unit, and developing player operation preference analysis facing the big data;
obtaining big data analysis results of player preference attributes associated with a particular gaming environment and executing various functional applications based on the results;
the player's operational data and the specific game environment data associated with the operational data are collected in any one or more of the following ways: obtaining a log recording player operation input content and input time thereof from a game application or service in real time; sampling the coordinate of a cursor clicking position of a player on a Graphical User Interaction (GUI) interface of a game at regular time, or touching the position coordinate in a touch game, and recording the position coordinate and sampling time as operation action process data; the method comprises the steps of sampling all objects existing in a specific game scene presented on a Graphical User Interaction (GUI) interface when a player operates at regular time, reading an object list, and inquiring and sampling state data of each object at regular time aiming at all objects related in the specific game scene presented when the player operates;
the intelligent device is provided with a user input coordinate interface matched with a Graphical User Interaction (GUI) interface, and position coordinates of each cursor click of a user or touch position coordinates are provided for the GUI interface; the plug-in of the game application or service can collect the coordinate value provided by the user input coordinate interface and transmit the coordinate value to the operation interface;
determining specific game environment data associated with the operational data by: extracting an object list and an object state contained in each specific game scene from each structured data storage file, labeling an environment mark for each specific game scene according to the difference degree of the object list and the object state, and labeling the same environment mark for scenes with the same game environment; and extracting recorded operation data from the structured data storage file, wherein the operation data comprises operation input content data and operation action process data, mapping the operation data to specific game scenes at the same acquisition time point according to the occurrence time of the operation input or the acquisition time of the operation action, and determining specific game environment data associated with the operation data according to the environment mark marked on each specific game scene.
5. The big-data based game player operation preference analysis method according to claim 4, wherein the degree of difference between the object list and the object state between the specific game scenes is judged as follows: judging whether the percentage of the same objects contained in two adjacent screens of specific game scenes in all the objects in each screen scene is lower than a threshold value or not, and if the percentage of at least one screen scene in the two screens of specific game scenes is lower than the threshold value, judging that the two screens of specific game scenes have different game environments; if the percentage of the same objects in all the objects contained in two adjacent scenes of the specific game is greater than or equal to the threshold value, then calculating the overall state difference degree of all the same objects in the two scenes by using the object state values; and if the overall state difference degree is greater than or equal to the threshold value, the two specific game scenes are judged to have different game environments, and if the overall state difference degree is lower than the threshold value, the two specific game scenes are judged to have the same game environment.
6. The big-data based game player operational preference analysis method of claim 5, wherein the functional application executed based on the big-data analysis result of the player preference attribute associated with the specific game environment comprises: a player assistance function of outputting necessary prompts to the assisted player based on the player operation preference under the specific game environment provided by the operation data analysis processing layer according to the specific game environment of the assisted player; or, a Graphical User Interaction (GUI) interface for implementing an optimized game optimizes interface options and button positions given to a specific game environment according to operational input preferences and operational action preferences of a player in the specific game environment.
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