Game Style Classification

Abstract

To analyze user game play data, histories, and taste.SOLUTION: A system for classifying a game style can track play of a user of one or multiple media contents. By analyzing tracked play of a user of one or multiple media contents, the user's play can be characterized based on one or multiple categories of a user game play style. Multiple categories of a user game play style are selected and can be displayed as visual display of a user game play style. The visual display of a user game play style can be compared with one or multiple visual displays of characteristics of other media contents. Recommendation of other media contents sharing characteristics that are similar to a user game play style can be generated.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates generally to analyzing user gameplay data, history, and preferences. More particularly, the present system relates to identifying gameplay patterns within various game titles played by a user and making custom predictions regarding other game titles. [Background technology]

[0002] 2. Description of Related Art Acquiring and playing a new game title can represent a significant investment of time, energy, and money by a player. An individual's budget and leisure time to devote to the games they choose to play can be limited. As a result, many consumers often seek advice or other types of research data from friends, review websites, gameplay streams, pre-recorded video content, walkthroughs, and other sources to obtain information about new game titles before purchasing them. Despite the additional effort made to determine whether a particular video game title may fit their individual interests and preferences, users may still find elements of the game undesirable and perceive it as a waste of time, energy, and resources.

[0003] Developers, manufacturers, digital distribution platforms, and hardcopy games may not provide enough information for users to distinguish a worthwhile experience from a waste of resources. Gameplay trailers, screenshots, and other media content from developers or manufacturers may unintentionally be misleading or depict gameplay that users cannot perform due to accessibility, skill level / experience, time available to overcome required gameplay obstacles, misrepresentation of gameplay flow, and numerous other issues. Digital distribution platforms used to purchase and download video games may generally include only a short text description of the content, a few relevant images or videos, and cursory reviews from other users with simplified star or point ratings. Such high-level descriptions may not provide further personalization with respect to the specific interests and characteristics of potential players. Without available consolidated and individualized information, players must perform time-consuming research that may or may not yield useful information.

[0004] Therefore, there is a need in the art for improved systems and methods for identifying gameplay patterns within various game titles played by a user and making customized predictions regarding other game titles. Summary of the Invention

[0005] Embodiments of the present invention may include systems and methods for classifying gameplay styles. An embodiment of a system for classifying gameplay styles may track a user's play of one or more media content. The user's tracked play of the one or more media content may be analyzed to identify one or more patterns and characterize the user's play based on one or more categories of the user's gameplay style. Multiple categories of the user's gameplay style may be selected and displayed as a visual representation of the user's gameplay style. The visual representation of the user's gameplay style may be compared to one or more visual representations of characteristics of other media content. Predictions or recommendations of other media content that share similar characteristics to the user's gameplay style may be generated.

[0006] In another embodiment, a method for categorizing a user's gaming style may be provided. Such a method may include tracking a user's gameplay records, detecting a categorization or classification of gameplay styles or gameplay preferences, generating a visual graphical representation of the categorization or classification, comparing the gameplay categorization with other games, generating a visual graphical analysis of the selected game categorization, displaying a representation of the selected game categorization overlaid or superimposed on the user's historical categorized gameplay preferences, generating and displaying predictions and recommendations of games similar to the categorized gameplay preferences, and displaying potential social connections with other users in a network based on the categorized gameplay preferences. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram of an exemplary network environment in which a system for classifying game styles may be implemented. [Figure 2]FIG. 1 is a diagram of an exemplary Uniform Data System (UDS) that may be used to provide data to a system for classifying gameplay styles. [Figure 3] 1 is a flowchart illustrating an exemplary method for identifying gameplay patterns within different game titles played by a user and making customized predictions regarding other game titles. [Figure 4] FIG. 1 is an exemplary data visualization of gameplay styles associated with users. [Figure 5] 5 is a diagram of an exemplary data visualization of game characteristics of one or more game titles overlaid on the data visualization of FIG. 4. [Figure 6] 10 is an exemplary display for providing recommendations for games that have gameplay characteristics that overlap with a user's identified gameplay style. [Figure 7] 10 is a flowchart illustrating an alternative method for identifying gameplay patterns within different game titles played by a user and making customized predictions regarding other game titles. [Figure 8] FIG. 1 is an exemplary data visualization of gameplay styles associated with users. [Figure 9] 10 is an exemplary display for providing recommendations for games that have gameplay characteristics that overlap with a user's identified gameplay style. [Figure 10] FIG. 1 is a block diagram of an exemplary electronic entertainment system that may be used to implement systems and methods for identifying game play patterns within different game titles played by a user and making customized predictions regarding other game titles. DETAILED DESCRIPTION OF THE INVENTION

[0008] A system and method for classifying gameplay styles is disclosed. The system may track a user's gameplay of one or more media content. The user's tracked gameplay of the one or more media content may be analyzed to identify gameplay patterns corresponding to one or more categories of gameplay styles. Multiple categories of user gameplay styles may be selected and displayed as a visual representation of the user gameplay style. The visual representation of the user gameplay style may be compared to one or more visual representations of characteristics of other media content. Recommendations of other media content that share similar characteristics to the user gameplay style may be generated.

[0009] FIG. 1 illustrates an exemplary network environment 100 in which a system for classifying game styles may be implemented. The network environment 100 may include one or more content source servers 100 providing digital content for distribution (e.g., games, other applications, and services), one or more content provider server application program interfaces (APIs) 120, a content delivery network server 130, a classification server 140, and one or more user devices 150. The servers described herein may include any type of server known in the art, including standard hardware computing components such as network and media interfaces, non-transitory computer-readable storage (memory), and a processor for executing instructions or accessing information that may be stored in the memory. The functionality of multiple servers may be integrated into a single server. Any of the aforementioned servers (or integrated servers) may exhibit specific client-side, cache, or proxy server characteristics. These characteristics may depend on the particular network placement of the servers or the particular configuration of the servers.

[0010] Content source server 110 may hold and provide a variety of digital content available for distribution. Content source server 110 may be associated with any content provider that makes its content available for access over a communications network. Such content may include digital video and games, as well as other types of digital applications and services. Such applications and services may include any of a variety of different digital content and functionality that may be provided to user device 150.

[0011] Content may be provided from content source servers 110 through content provider server APIs 120, enabling various types of content source servers 110 to communicate with other servers (e.g., user devices 150) within the network environment 100. The content provider server APIs 120 may be specific to the content source server 110 providing the content and to the particular language, operating system, protocol, etc. of the user device 150. In a network environment 100 that includes multiple different types of content source servers 110, there may likewise be a corresponding number of content provider server APIs 120 that enable various formatting, conversion, and other cross-device and cross-platform communication processes to provide content and other services to different user devices 150 that may use different operating systems, protocols, etc. to process such content. Thus, applications and services may be made available in different formats to be compatible with a variety of different user devices 150.

[0012] The content provider server API 120 may further facilitate each of the user devices 150's access to content hosted by the content source server 110 or to services provided by the content source server 110, either directly or via the content delivery network server 130. Additional information, such as metadata about the accessed content or service, may also be provided to the user device 150 by the content provider server API 120. As described below, the additional information (i.e., metadata) may be available to provide details about the content or service being provided to the user device 150. In some embodiments, the services provided by the content source server 110 to the user device 150 via the content provider server API 120 may include support services associated with other content or services, such as chat services, ratings, and profiles associated with particular games, teams, communities, etc. In such cases, the content source servers 110 may also communicate with each other via the content provider server API 120.

[0013] The content delivery network servers 130 may include servers that provide resources, files, etc. related to content from the content source servers 110, including various content and service configurations, to user devices 150. The content delivery network servers 130 may also be invoked by user devices 150 requesting access to specific content or services. The content delivery network servers 130 may include universe management servers, game servers, streaming media servers, servers hosting downloadable content, and other content delivery servers known in the art.

[0014] Classification server 140 may include any data server known in the art capable of classifying game styles. In an exemplary implementation, classification server 140 may retrieve and store user profiles containing historical user data about users of user devices 150. Such historical user data may relate to the media content with which the user interacted in each historical gameplay session and may include data such as game titles played, total time played, time played per session, time played in single player or multiplayer mode, teammates or rivals, time to complete each level (e.g., activity), activities attempted and completed, as well as title-specific and activity-specific data (e.g., character deaths or failure rates), mandatory and voluntary objective completion rates, behavioral preferences (e.g., melee combat, run-and-gun, exploration), selected difficulty settings, and other statistics dependent on the particular media content.

[0015] Additionally, classification server 140 may store data related to characteristics of the media content, which may include data specific to the media content, such as genre data (e.g., puzzle, third-person shooter, platformer, cinematic), available game modes (e.g., competitive, player versus environment), types of in-game activity, metrics for measuring in-game status and progress, and other characteristics that depend on the title of the individual media content.

[0016] In an example implementation of the present invention, classification server 140 may perform an analysis of historical user data to identify one or more gameplay patterns associated with specific game titles or in-game activities in which the user participated. Such gameplay patterns may be converted into a data visualization display that shows how the identified gameplay patterns correspond to different gameplay categories. Such data visualizations (and displayed gameplay categories) may be specific to a particular game title, a particular genre of game title, a particular time frame, or any other combination of categories that correspond to gameplay patterns.

[0017] Additionally, classification server 140 may generate overlays corresponding to different game titles and associated characteristics. When a particular game title is overlaid on a data visualization of gameplay patterns associated with a user, it may be determined whether or not it contains characteristics corresponding to the user's gameplay patterns. Thus, a prediction may be made as to how likely the user is to be interested in and enjoy playing a particular game title. Such data visualizations and overlays may be provided to the user (via user device 150) and may also be shared with other individuals and entities (via corresponding user devices 150). In various embodiments, a custom notification may be generated that includes such data visualizations and overlays, as well as a custom prediction or recommendation regarding a specific game title. Such a custom notification (and custom prediction or recommendation) may include a summary of the identified gameplay patterns and an explanation of how the gameplay patterns correspond (and / or do not correspond) to the game title.

[0018] The user devices 150 may include multiple different types of computing devices. The user devices 150 may be servers that provide internal services (e.g., to other servers) in the network environment 100. In such cases, the user devices 150 may correspond to one of the content servers 110 described herein. Alternatively, the user devices 150 may be client devices, which may include any number of different game consoles, mobile devices, laptops, and desktops. Such user devices 150 may also be configured to access data from other storage media, such as, but not limited to, memory cards or disk drives, which may be appropriate in the case of downloaded services. Such user devices 150 may include standard hardware computing components, such as, but not limited to, network and media interfaces, non-transitory computer-readable storage (memory), and a processor that executes instructions that may be stored in memory. These user devices 150 may also operate using a variety of different operating systems (e.g., iOS, Android®), applications, or computing languages ​​(e.g., C++, JavaScript®). Each user device 150 may be associated with a participant or other type of observer of a collection of digital content streams.

[0019] FIG. 2 illustrates an exemplary Uniform Data System (UDS) 200 that can be used to provide data to a system for classifying gameplay styles. Based on the data provided by the UDS, a game style server can classify users by recognizing which in-game objects, entities, activities, and events they have engaged with, thus supporting analysis and adjustment of in-game activities. Each user interaction can be associated with metadata such as the type of in-game interaction, its location within the in-game environment, and its time point within the in-game timeline, as well as other players, objects, and entities involved. Thus, metadata can be tracked for any of a variety of user interactions that may occur during a game session, including associated activities, entities, settings, results, actions, effects, locations, and character statistics. Such data can be further aggregated and applied to a data model for analysis. Such a UDS data model can be used to assign contextual information to pieces of information in a uniform manner across the game.

[0020] 2, an exemplary console 228 and an exemplary server 218 (including a streaming service 220, an activity feed server 224, a user-generated content (UGC) server 232, and an object server 226) are shown. In different embodiments, the console 228 may be implemented on the content source server 110, a cloud server, any of the servers 218, or a user device 150. In an exemplary example, a content recorder 202 may be implemented on the content source server 110, a cloud server, or any of the servers 218. Such a content recorder 202 receives content (e.g., media) from an interactive content title 230 and records it on a content ring buffer 208. Such a ring buffer 208 may store multiple content segments (e.g., v1, v2, and v3), a start time for each segment (e.g., V1_START_TS, V2_START_TS, V3_START_TS), and an end time for each segment (e.g., V1_END_TS, V2_END_TS, V3_END_TS). Such segments may be stored as media files 212 (e.g., MP4, WebM, etc.) by the console 228. Such media files 212 may be uploaded to the streaming server 220 for storage and subsequent streaming or use, although the media files 212 may be stored on any server, cloud server, any console 228, or any user device 150. The start and end times for each such segment may be stored by the console 228 as a content timestamp file 214. Such content timestamp file 214 may also include a stream ID that matches the stream ID of the media file 212, thereby associating the content timestamp file 214 with the media file 212.Such content timestamp files 214 may be uploaded and stored on the activity feed server 224 and / or the UGC server 232, but the content timestamp files 214 may be stored on any server, cloud server, any console 228, or any user device 150.

[0021] While the content recorder 202 receives and records content from the interactive content title 230, the object library 204 receives data from the interactive content title 230, and the object recorder 206 tracks the data to determine when an object begins and ends. The object library 204 and the object recorder 206 may be implemented on the content source server 110, a cloud server, or any server 218. When the object recorder 206 detects the start of an object, it receives object data from the object library 204 (e.g., if the object is an activity, the user interaction with the activity, the activity ID, the activity start time, the activity end time, the activity result, the activity type, etc.) and records this activity data on the object ring buffer 210 (e.g., ActivityID1, START_TS; ActivityID2, START_TS; ActivityID3, START_TS). Such activity data recorded on the object ring buffer 210 may be stored in an object file 216. Such object files 216 may also include activity start time, activity end time, activity ID, activity result, activity type (e.g., competitive match, quest, task, etc.), and user or peer data related to the activity. For example, object files 216 may store data regarding items used during the activity. Such object files 216 may be stored on an object server 226, although object files 216 may be stored on any server, cloud server, any console 228, or any user device 150.

[0022] Such object data (e.g., object files 216) can be associated with content data (e.g., media files 212 and / or content timestamp files 214). In one example, the UGC server 232 stores the content timestamp files 214 in association with the object files 216 based on a match between the stream ID of the content timestamp files 214 and the corresponding activity ID of the object files 216. In another example, the object server 226 can store the object files 216 and receive queries for the object files 216 from the UGC server 232. Such queries can be performed by searching for an activity ID of the object files 216 that matches the stream ID of the content timestamp files 214 sent with the query. In yet another example, queries of the stored content timestamp files 214 can be performed by matching the start and end times of the content timestamp files 214 with the start and end times of the corresponding object files 216 sent with the query. Such object files 216 may also be associated with matching content timestamp files 214 by the UGC server 232, although this association may be performed by any server, cloud server, any console 228, or any user device 150. In another example, the object files 216 and content timestamp files 214 may be associated by the console 228 during creation of each file 216, 214.

[0023] In an exemplary embodiment of the invention, the activity file 216 generated by the UDS system 200 may be provided to the classification server 140 as part of historical gameplay data associated with a user. Such an activity file 216 may be provided for each game session in which the user engaged in gameplay. Thus, the classification server 140 may be able to identify specific gameplay activities within a game title and identify relevant in-game parameters associated with the activity, including the type of challenge or obstacle, the type and amount of actions taken by the user, how success or failure is measured, what virtual objects, environments, or characters were involved, and other parameters relevant to the specific game title or activity. Each of the parameters may be analyzed in conjunction with the activity file from the user's past gameplay sessions to determine whether any gameplay patterns can be identified. Such gameplay patterns may also be compared to patterns associated with other users to identify similarities and differences therebetween. In such cases, the historical gameplay data of other users may also be used to identify the user's gameplay patterns and to generate predictions and recommendations.

[0024] FIG. 3 is a flowchart illustrating an example method 300 for identifying gameplay patterns within various game titles played by a user and making customized predictions regarding other game titles. Method 300 may be executed by classification server 140 to analyze game characteristics and patterns of user engagement. At step 310, classification server 140 may receive data from UDS 200 to determine various game characteristics of one or more games. At step 320, UDS 200 may transmit recorded data regarding the user's interactions with one or more games to classification server 140. Classification server 140 may further analyze the user's interactions with one or more games to determine characteristics of the games played by the user. At step 330, classification server 140 may determine common characteristics shared among one or more games in which the user has engaged. Furthermore, classification server 140 may determine common characteristics of games played by users segmented into one or more game genres.

[0025] In step 340, game characteristics within one or more games or one or more genres of games played by the user obtained from step 330 may be determined as preferred characteristics based on the weighted game preferences. The weighted game preferences may be determined by classification server 140 by detecting repeated patterns in the content the user engages with, length of engagement with content types, and other data reported by UDS 200 as consistent behavioral characteristics of the user's interactions with one or more games. For example, a user may have engaged in a variety of role-playing games (RPGs) in their gameplay history. In most of the RPGs in which the user has engaged, in-game combat may be turn-based. Based on the user's involvement in several games in the RPG genre and the majority of those games including turn-based combat systems, classification server 140 may determine the user's preferred characteristic to be turn-based combat.

[0026] At step 350, favorable game characteristics common to the one or more games provided at step 340 may be determined to be important to the user based on the previously determined weights, and a data visualization may be generated for display. Further, classification server 140 may compare the generated game characteristics with one or more games not engaged with the user at step 360 and display the generated comparison. Finally, classification server 140 may provide recommendations to the user at step 370 based on the comparison of the common generated characteristics. The recommendations may include superimposed or overlaid data visualizations that display the common generated characteristics of games in the user's gameplay history along with other games not yet engaged with the user.

[0027] 4 shows an example data visualization 400 of a gameplay style associated with a user. Once the user's preferred game characteristics are generated by classification in game style server 140, as described above in process 300, data visualization 400 may be presented via a graphical user interface (GUI) on the display of user device 150. Various types of data visualization displays may be generated to help the user understand the classification of game styles based on game characteristics.

[0028] In one embodiment, the user's preferred game characteristics are plotted on a hexagonal radar chart 410. A label for each of the user's 420 preferred game characteristics may be displayed adjacent to each vertex. The game characteristics plotted within the hexagonal radar chart 410 may indicate that points plotted closer to the vertex 430 represent a stronger presence of the game characteristic in the game, while points plotted closer to the center represent a weaker presence of the game characteristic in the game. However, it should be noted that the game characteristic measurements and the plotted points associated with the game characteristics may represent various types of information. For example, plotted point 440 may represent a stronger presence of a competitive characteristic in the game, and plotted point 450 may represent a shorter time to complete a match or game in a peer-to-peer (P2P) gameplay mode. Furthermore, point 460 may represent a medium level of difficulty for one or more game characteristics.

[0029] 5 shows exemplary data visualizations 500 and 520 of game characteristics for one or more game titles overlaid on the data visualization of FIG. 4. The data visualization 400 of the user's preferred game characteristics may be overlaid, combined, or otherwise compared to data visualizations of one or more additional games. The manner in which the game characteristics are compared may be determined based on the selected data visualizations generated by classification server 140.

[0030] In one embodiment, a user may view one or more games that they have not previously played, and an overlap data visualization 500 comparing preferred game characteristics with the selected game may be displayed in the GUI of the user device 150. The user may choose to view games in a variety of ways, including, but not limited to, a digital store catalog, a social connection list, or an in-game menu of a demonstration or trial game. The classification server 140 may combine the user's preferred game characteristics visualization 400 with the selected game 510 by displaying a plot of the same game characteristics as the detected set of the user's preferred game characteristics for the selected game. Furthermore, one or more additional games may be simultaneously selected, displaying an additional data visualization 520 with the plotted game characteristics of the additional selected game 530. Similarities and differences between the game characteristics of the selected game 510 or 530 and the user's 400 preferred game characteristics may be visually compared.

[0031] Additionally, classification server 140 may detect details of the compared data visualizations of one or more games and generate a message 540 for display via the GUI of user device 150. Message 540 may convey information displayed in selected data visualization 500 or 520 to the user to aid in interpreting the compared game characteristics of one or more games. For example, information regarding similar data points of the characteristics of the selected game compared to the user's preferred game characteristics may be outlined in a first message 550. Additionally, differences in the characteristics of the selected game compared to the user's preferred game characteristics may be outlined in a second message 560.

[0032] 6 shows an example display for providing recommendations of games that have gameplay characteristics that overlap with a user's identified gameplay style. In addition to comparing the data visualization of the user's preferred gameplay characteristics with one or more other games, as in 500 and 520, classification server 140 may compare gameplay characteristics between one or more games based on the user's preferred gameplay characteristics.

[0033] In one embodiment, classification server 140 may detect genres or games and weighted factors for the user based on data received from UDS 200, such as extended overall play time, and may determine preferred game characteristics associated with the game or genre described above in steps 340 and 350 of FIG. 3. Utilizing the user's determined preferred game characteristics, classification server 140 may further compare one or more games with the game characteristics described in step 360. One or more games that share characteristics similar to the game or genre of the preferred game characteristics may be compared and overlaid on data visualization 600. A first game 610 in which the user previously engaged may be overlaid or superimposed with a second game 620 in which the user has not yet engaged, and characteristics related to the first and second games and related to the user's preferred game characteristics may be displayed in data visualization 600.

[0034] Additionally, classification server 140 may display a message 630 informing the user about a comparison of the first game and the second game with respect to preferred game characteristics. The recommendation may be provided via message 630 or other on-screen prompt associated with a data visualization of the compared games 600. A call to action 640 to engage with the recommendation may be displayed using a button prompt or other user input required to proceed with play of the second game provided by the recommendation. Classification server 140 may further process gameplay data received from UDS 200 related to the user's preferred gameplay style in one or more games.

[0035] FIG. 7 is a flowchart illustrating an alternative method 700 for identifying gameplay patterns within various game titles played by a user and making customized predictions regarding other game titles. Method 700 may be executed by classification server 140 to determine a user's preferred gameplay style. Classification server 140 may receive data related to the gameplay styles of one or more games from UDS 200. Various categories of gameplay styles may be determined at step 710 based on data captured by UDS 200. Interactions with in-game objects, entities, activities, and events provided to classification server 140 by UDS 200 may be utilized to analyze user gameplay style preferences across one or more games at step 720. Additionally, at step 730, classification server 140 may correlate the preferences obtained from step 720 across one or more games to determine the user's preferred game style across all games played. The preferred game style may be further analyzed to determine the user's preferences across one or more game genres. At step 740, classification server 140 may determine the user's preferred gaming style category for the game and genre analyzed at step 730 by assigning weights to preferred gaming styles. The preferred gaming style weighting may be determined by consistent preferences detected throughout the user's gameplay of one or more games. For example, a user who engages in similar activities repeatedly within a game or across multiple games may be analyzed for a weighted preference in the user's gaming style. Furthermore, as more data is collected by UDS 200 and the user continues to engage in similar activities, the associated weighted preference for the activity may be determined to be important to the user, with the importance increasing as the user engages more frequently and consistently in the activity or behavior.

[0036] In an exemplary embodiment, a user may be involved in multiple single-player games. Each single-player game in which a user is involved may include required activities that the player must complete to progress through the game, as well as optional activities that the player may complete in addition to game bonuses, content, or character progression. Throughout the user's playtime history, UDS 200 may capture and report engagement in required and optional activities to classification server 140. A user may choose to complete optional activities in addition to required activities in one or more single-player games. A user may also complete each required activity of one or more games and then "finish" the required content of one or more games that require completion. Classification server 140 may determine a user's weighted, consistent playing style as a "completionist," i.e., a user who prefers to complete both required and optional activities that involve the majority of content that may be available in a game's defined activity.

[0037] The user's preferred gaming style determined in step 740 may be utilized by classification server 140 to provide additional content, recommendations, and present users with information regarding their preferred gaming style. Exemplary embodiments and uses of preferred gaming style categories follow steps 750, 760, and 770 and are further detailed in Figures 8 and 9.

[0038] In one embodiment, classification server 140 may display the user's preferred game style categories in a data visualization, as in step 750. The display of preferred game style categories may be displayed to the user via a GUI of user device 150. For example, it may be displayed to indicate the user's game style preferences for combat types, activity paths, and character advancement in an action RPG.

[0039] 8 shows an example data visualization 800 of gameplay styles associated with a user. The user's preferred game style may be displayed as data visualization 800. The user's preferred game style categories may be plotted on a hexagonal radar chart 810. A label 830 for each preferred game style category may be displayed adjacent to each vertex 820. The preferred game styles plotted within the hexagonal radar chart 810 may indicate that points plotted closer to the vertices 820 represent a strong preference for the user to perform actions associated with the game style in the game, while points plotted closer to the center of the chart may represent a weaker preference for the game style in the game.

[0040] FIG. 9 shows an exemplary display 900 for providing recommendations 930 of games that have gameplay characteristics that overlap with the user's identified gameplay style. A representation of a user's preferred game style, such as that generated in FIG. 8, may be compared to one or more games by classification server 140. A data visualization 900 may be generated to compare and recommend one or more games similar to the user's preferred game style. A representation 910 of the user's preferred game style categories may be overlaid or superimposed on a representation 920 of the game styles of one or more games. The data visualization 900 may be displayed to the user by classification server 140 via the GUI of user device 150. Classification server 140 may provide recommendations to the user related to games that have available gameplay similar to the user's preferred game style categories. One or more games may be selected for comparison by classification server 140. The games selected for comparison with a first game played by the user may be displayed to highlight that the user may utilize the preferred game style category in a second game. A message 930 may be displayed along with the data visualization to inform the user of games with similar game style categories and guide them to access content.

[0041] In another embodiment, classification server 140 may provide recommendations to users associated with social connections in one or more games. A user's preferred gaming style, with preferences for games or types of gameplay that may complement or complement other similar users, may be determined in step 770 of FIG. 7. A list of similar complementary users may be displayed to the user by classification server 140 via a GUI on user device 150. Social contacts may be recommended via the list for matchmaking in one or more games that may be beneficial to the user, enabling them to utilize their preferred gaming style with other users.

[0042] Figure 10 is a block diagram of an exemplary electronic entertainment system 1000 that may be used to implement systems and methods for identifying gameplay patterns within various game titles played by a user and making customized predictions regarding other game titles. The entertainment system 1000 of Figure 10 includes a main memory 1005, a central processing unit (CPU) 1010, a vector unit 1015, a graphics processing unit 1020, an input / output (I / O) processor 1025, an I / O processor memory 1030, a controller interface 1035, a memory card 1040, a universal serial bus (USB) interface 1045, and an IEEE interface 1050. The entertainment system 1000 further includes an operating system read-only memory (OS ROM) 1055, an audio processing unit 1060, an optical disc control unit 1070, and a hard disk drive 1065, which are connected to the I / O processor 1025 via a bus 1075.

[0043] Entertainment system 1000 may be an electronic game console. Alternatively, entertainment system 1000 may be implemented as a general-purpose computer, a set-top box, a handheld gaming device, a tablet computing device, or a mobile computing device or mobile phone. Entertainment systems may include more or fewer operating components depending on the particular form factor, purpose, or design.

[0044] The CPU 1010, vector unit 1015, graphics processing unit 1020, and I / O processor 1025 of FIG. 10 communicate via a system bus 1085. Additionally, the CPU 1010 of FIG. 6 may communicate with main memory 1005 via a dedicated bus 1080, and the vector unit 1015 and graphics processing unit 1020 may communicate via a dedicated bus 1090. The CPU 1010 of FIG. 10 executes programs stored in the OS ROM 1055 and the main memory 1005. The main memory 1005 of FIG. 10 may include pre-stored programs and programs transferred via the I / O processor 1025 from a CD-ROM, DVD-ROM, or other optical disk (not shown) using the optical disk control unit 1070. The I / O processor 1025 of FIG. 10 may also enable the introduction of content transferred via wireless or other communication networks (e.g., 4G, LTE, 3G, etc.). The I / O processor 1025 of FIG. 10 primarily controls the exchange of data between various devices of the entertainment system 1000, including the CPU 1010, the vector unit 1015, the graphics processing unit 1020, and the controller interface 1035.

[0045] The graphics processing unit 1020 of Figure 10 executes graphics instructions received from the CPU 1010 and the vector unit 1015 to generate images for display on a display device (not shown). For example, the vector unit 1015 of Figure 10 may convert an object from three-dimensional coordinates to two-dimensional coordinates and send the two-dimensional coordinates to the graphics processing unit 1020. Additionally, the audio processing unit 1060 executes instructions to generate audio signals that are output to an audio device, such as a speaker (not shown). Other devices may be connected to the entertainment system 1000 via the USB interface 1045 and the IEEE interface 1050, such as a wireless transceiver, which may be embedded within the system 1000 or as part of some other component, such as a processor.

[0046] 10 provides instructions to the CPU 1010 via the controller interface 1035. For example, the user may instruct the CPU 1010 to store certain game information on a memory card 1040 or other non-transitory computer-readable storage medium, or to instruct a character in a game to perform some specified action.

[0047] The system may be implemented in an application that may be operable by a variety of end-user devices. For example, the end-user device may be a personal computer, a home entertainment system (e.g., Sony PlayStation2® or Sony PlayStation3® or Sony PlayStation4® or Sony PlayStation5®), a portable gaming device (e.g., Sony PSP® or Sony Vita®), or a home entertainment system from a different, but subordinate, manufacturer. It is fully contemplated that the methods described herein will be operable on a variety of devices. The system may also be implemented in a cross-title neutral manner, such that embodiments of the system may be utilized in a variety of titles from a variety of publishers.

[0048] The system may be implemented in an application that may be operable using a variety of devices. A non-transitory computer-readable storage medium refers to any medium or media that participates in providing instructions to a central processing unit (CPU) for execution. Such media may take many forms, including but not limited to non-volatile and volatile media, such as optical or magnetic disks and dynamic memory, respectively. Common forms of non-transitory computer-readable media include, for example, a floppy disk, a flexible disk, a hard disk, magnetic tape, any other magnetic media, a CD-ROM disk, a digital video disk (DVD), any other optical media, a RAM, a PROM, an EPROM, a FLASHEPROM, and any other memory chip or cartridge.

[0049] Various forms of transmission media may be involved in carrying one or more sequences of one or more instructions to the CPU for execution. A bus carries the data to system RAM, and the CPU retrieves and executes the instructions from the system RAM. The instructions received by the system RAM may optionally be stored on a fixed disk either before or after execution by the CPU. Various forms of storage may also be implemented, along with network interfaces and network topologies necessary to implement the storage.

[0050] The above detailed description of the present technology has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the present technology to the precise form disclosed. Many modifications and variations are possible in light of the above teachings. The described embodiments were selected to best explain the principles of the technology, its practical application, and to enable those skilled in the art to utilize the technology in various embodiments and with various modifications suitable for the particular uses contemplated. It is intended that the scope of the present technology be defined by the claims.

Claims

1. 1. A method for classifying gameplay styles, comprising: receiving data regarding gameplay by users who have played one or more media content titles, the data being received over a communications network; storing the received data in a memory, the received data being included in a dataset of historical gameplay data associated with the user; Executing instructions stored in a memory, the instructions being executed by a processor to: identifying one or more gameplay patterns in the historical gameplay data; identifying the gameplay patterns as corresponding to one or more categories of gameplay styles; generating a visual display including a data visualization of the identified gameplay patterns corresponding to the identified categories of gameplay styles; updating the visual display to overlay a graphical representation of a predetermined characteristic of at least one media content title onto the data visualization of the identified category of gameplay style; Including, the data visualization showing the weight of the identified categories in the identified gameplay patterns; The method, wherein the graphical representation shows weights of characteristics consistent with the identified categories of at least one media content title in comparison to weights of the identified categories in the identified gameplay patterns.

2. storing information about a plurality of different media content titles, the stored information including a plurality of predetermined characteristics of each media content title; comparing the identified category of gameplay style to at least one predetermined characteristic of the media content title; 2. The method of claim 1, further comprising: generating a prediction based on an identification that the predetermined characteristic of at least one media content title corresponds to the identified category of gameplay style based on the comparison, wherein updating the visual display is based on the prediction.

3. The method of claim 2 , further comprising updating the visual display to include a recommendation for the at least one media content title based on the prediction.

4. 4. The method of claim 3, further comprising updating the visual display to overlay a graphical representation of the predetermined characteristic of at least one media content title with a graphical representation of a predetermined characteristic of one of the media content titles played by the user.

5. 4. The method of claim 3, wherein the recommendation includes at least one of a statement that the predetermined characteristic of at least one media content title matches the identified category of gameplay style or a statement that the predetermined characteristic of at least one media content title matches the identified category of gameplay style.

6. 3. The method of claim 2, wherein the identified category of gameplay style is compared to the predetermined characteristics of a plurality of media content titles, and the predetermined characteristics of the at least one media content title is identified as having the greatest number of matches with the identified category of gameplay style.

7. 10. The method of claim 1, wherein the gameplay pattern includes one or more of the media content titles identified as preferred by the user, and further comprising identifying one or more characteristics common to the identified media content titles.

8. 8. The method of claim 7, further comprising identifying a subset of the characteristics for inclusion in the data visualization by weighting one or more factors associated with the characteristics of the identified media content titles.

9. The method of claim 8 , further comprising filtering other predetermined characteristics of the identified media content titles based on the weighted factors.

10. The method of claim 8 , wherein the factors include at least one of play duration, captured sensor data about the user, and genre of the identified media content title.

11. The method of claim 1 , wherein identifying the gameplay pattern is further based on historical gameplay data of one or more other peers associated with the user.

12. 10. The method of claim 1, further comprising updating the visual display to include peer recommendations comprising a data visualization of identified gameplay patterns of peers overlaid on the data visualization of the identified categories of gameplay styles.

13. The method of claim 11 , further comprising identifying the peer based on one or more identified gameplay patterns associated with the one or more other peers.

14. The method of claim 13 , wherein the identified gameplay patterns associated with the one or more other peers match at least one of the identified gameplay patterns of the user.

15. 1. A system for classifying game styles, comprising: Memory and A processor that executes instructions stored in a memory, wherein execution of the instructions by the processor comprises: receiving a user's play of one or more media content; characterizing the play based on one or more categories of user game play style; generating a visual display including a data visualization of said one or more categories of gameplay styles; updating the visual display to overlay a graphical representation of predetermined characteristics of at least one media content title onto the data visualization of identified categories of gameplay styles; Equipped with the data visualization showing the weights of the identified categories in the characterized plays; The graphical representation illustrates weights of characteristics consistent with the identified categories of at least one media content title, comparable to weights of the identified categories in the characterized play.

16. A non-transitory computer-readable storage medium having embodied thereon a program executable by a processor to perform a method for classifying game styles, the method comprising: receiving data regarding gameplay by users who have played one or more media content titles, the data being received over a communications network; storing the received data in a memory, the received data being included in a dataset of historical gameplay data associated with the user; Executing instructions stored in a memory, said instructions being executed by a processor to: identifying one or more gameplay patterns in the historical gameplay data; identifying the gameplay patterns as corresponding to one or more categories of gameplay styles; generating a visual display including a data visualization of the identified gameplay patterns corresponding to the identified categories of gameplay styles; updating the visual display to overlay a graphical representation of a predetermined characteristic of at least one media content title onto the data visualization of the identified category of gameplay style; Including, the data visualization showing the weight of the identified categories in the identified gameplay patterns; A non-transitory computer-readable storage medium, wherein the graphical representation shows weights of characteristics consistent with the identified categories of at least one media content title in a manner comparable to weights of the identified categories in the identified gameplay patterns.

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