CN105477860A - Game activity recommending method and device - Google Patents
Game activity recommending method and device Download PDFInfo
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- CN105477860A CN105477860A CN201510971743.8A CN201510971743A CN105477860A CN 105477860 A CN105477860 A CN 105477860A CN 201510971743 A CN201510971743 A CN 201510971743A CN 105477860 A CN105477860 A CN 105477860A
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
- A63F2300/50—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers
- A63F2300/55—Details of game data or player data management
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
- A63F2300/50—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterized by details of game servers
- A63F2300/55—Details of game data or player data management
- A63F2300/5546—Details of game data or player data management using player registration data, e.g. identification, account, preferences, game history
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Abstract
The invention discloses a game activity recommending method and device. The method includes the steps of obtaining user data of a plurality of users and game data of a plurality of games through data mining, generating user images of all the users according to the user data, generating game images of all the games according to the game data, matching the user image of each user with the game images of the games, obtaining the matched game, obtaining the activity corresponding to the matched game, and recommending the activity corresponding to the matched game to the user. By means of the scheme, the game activities are intelligently recommended, the recommending effect of the game activities is improved, and the recommending mode of the game activities is optimized.
Description
Technical field
The present invention relates to Internet technical field, be specifically related to a kind of ludic activity recommend method and device.
Background technology
Along with improving constantly of people's living standard, the entertainment requirements of people is also more and more higher, and increasing people like playing games at free time.Therefore, gaming operators are in order to meet the game demand of people, be proposed various game, and in order to promote that people participate in game more energetically, corresponding ludic activity is also proposed for every money game, and can by propelling movement, displaying or other modes to the activity of user's recommended games.
But, in the prior art, such as play for certain money, what gaming operators was recommended to all users that this game is correlated with by gaming platform, game center, game webpage etc. is all whole ludic activities of this game, such as to user it is recommended that this game all supplement activity with money, but not considering user, whether to supplement activity with money to these all interested, therefore, be difficult to obtain good ludic activity recommendation effect, cause the waste recommending resource.
Summary of the invention
In view of the above problems, propose the present invention to provide a kind of overcoming the problems referred to above or the ludic activity recommend method solved the problem at least in part and device, achieve the intelligent recommendation of ludic activity, improve the recommendation effect of ludic activity.
According to an aspect of the present invention, provide a kind of ludic activity recommend method, the method comprises:
The user data of multiple user and the game data of multiple game is obtained by data mining;
User's portrait of each user is generated according to user data;
The game portrait of each game is generated according to game data;
For one of them user in multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, give this user by the activity recommendation of the game correspondence of coupling.
According to a further aspect in the invention, provide a kind of ludic activity recommendation apparatus, this device comprises:
First acquisition module, is suitable for obtaining the user data of multiple user and the game data of multiple game by data mining;
First generation module, the user data being suitable for obtaining according to the first acquisition module generates user's portrait of each user;
Second generation module, the game data being suitable for obtaining according to the first acquisition module generates the game portrait of each game;
Matching module, is suitable for for one of them user in multiple user, mating, obtaining the game of mating by being drawn a portrait with the game of multiple game by the user of this user portrait;
Second acquisition module, is suitable for for one of them user in multiple user, obtains the activity of the game correspondence of coupling;
Recommending module, is suitable for for one of them user in multiple user, and the activity recommendation of the game correspondence of the coupling obtained by the second acquisition module gives this user.
According to technical scheme provided by the invention, the user data of multiple user and the game data of multiple game is obtained by data mining, then user's portrait of each user and the game portrait of each game is generated according to user data and game data respectively, last for one of them user in multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, give this user by the activity recommendation of the game correspondence of coupling.User's portrait mates with game portrait by technical scheme provided by the invention, obtain the game of the coupling of certain user applicable, this user is given by the activity recommendation of the game correspondence of coupling, thus achieve the intelligent recommendation of ludic activity, improve the recommendation effect of ludic activity, optimize the way of recommendation of ludic activity.
Above-mentioned explanation is only the general introduction of technical solution of the present invention, in order to technological means of the present invention can be better understood, and can be implemented according to the content of description, and can become apparent, below especially exemplified by the specific embodiment of the present invention to allow above and other objects of the present invention, feature and advantage.
Accompanying drawing explanation
By reading hereafter detailed description of the preferred embodiment, various other advantage and benefit will become cheer and bright for those of ordinary skill in the art.Accompanying drawing only for illustrating the object of preferred embodiment, and does not think limitation of the present invention.And in whole accompanying drawing, represent identical parts by identical reference symbol.In the accompanying drawings:
Fig. 1 shows the schematic flow sheet of ludic activity recommend method according to an embodiment of the invention;
Fig. 2 shows the schematic flow sheet of ludic activity recommend method in accordance with another embodiment of the present invention;
Fig. 3 shows the illustrative view of functional configuration of ludic activity recommendation apparatus according to an embodiment of the invention.
Detailed description of the invention
Below with reference to accompanying drawings exemplary embodiment of the present disclosure is described in more detail.Although show exemplary embodiment of the present disclosure in accompanying drawing, however should be appreciated that can realize the disclosure in a variety of manners and not should limit by the embodiment set forth here.On the contrary, provide these embodiments to be in order to more thoroughly the disclosure can be understood, and complete for the scope of the present disclosure can be conveyed to those skilled in the art.
Fig. 1 shows the schematic flow sheet of ludic activity recommend method according to an embodiment of the invention, and as shown in Figure 1, the method comprises the steps:
Step S100, obtains the user data of multiple user and the game data of multiple game by data mining.
In the step s 100, the mode such as to get ready by large data analysis, data and carry out data mining, obtain the user data of multiple user and the game data of multiple game.
Step S101, generates user's portrait of each user according to user data.
After step S100 obtains the user data of multiple user, in step S101, generate user's portrait of each user according to user data.Wherein, user property can be known exactly by user's portrait.
Step S102, generates the game portrait of each game according to game data.
After step S100 obtains the game data of multiple game, in step s 102, the game portrait of each game is generated according to game data.Wherein, game attributes can be known exactly by game portrait.
Step S103, for one of them user in multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, give this user by the activity recommendation of the game correspondence of coupling.
After the game portrait of the user's portrait and each game that generate each user, in step s 103, for one of them user in multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, then the activity of the game correspondence of coupling is obtained, this user is given by the activity recommendation of the game correspondence of coupling, that is, what recommend this user is that this user may activity corresponding to more interested game, thus achieves the intelligent recommendation of ludic activity.
According to the ludic activity recommend method that the present embodiment provides, the user data of multiple user and the game data of multiple game is obtained by data mining, then user's portrait of each user and the game portrait of each game is generated according to user data and game data respectively, last for one of them user in multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, give this user by the activity recommendation of the game correspondence of coupling.User's portrait mates with game portrait by technical scheme provided by the invention, obtain the game of the coupling of certain user applicable, this user is given by the activity recommendation of the game correspondence of coupling, thus achieve the intelligent recommendation of ludic activity, improve the recommendation effect of ludic activity, optimize the way of recommendation of ludic activity.
Fig. 2 shows the schematic flow sheet of ludic activity recommend method in accordance with another embodiment of the present invention, and as shown in Figure 2, the method comprises the steps:
Step S200, obtains the user's characteristic information of multiple user, user preference information, user charges information and user's game records information by data mining.
In step s 200, the mode such as to get ready by large data analysis, data and carry out data mining, obtain the user data such as the user's characteristic information of multiple user, user preference information, user charges information and user's game records information.
Particularly, user's characteristic information comprises: user's inherent feature and user sources channel; User preference information comprises: user browses preference information, user clicks preference information and user's liveness information; User charges information comprises: user charges recorded information and user charges potentiality information; User's game records information comprises: user participates in game information and user's game ratings information.Wherein, user's inherent feature comprises: the features such as user's sex, age of user and user's constellation.
In addition, in order to the game of multianalysis user is liked, user preference information also can comprise: create role's preference information etc. in type of play preference information, game subject matter characteristic preference information, game fine arts style preferences information, game picture preference information, game fight mode preference information, game setting preference information, game IP preference information, game level preference information, game developer's preference information, game visual angle preference information, sound effect of game preference information, game size preference information and game.Such as, some users like action game, then the type of play preference information of this user can operation of recording class be played; Some users like the game of imperial palace subject matter, then the game subject matter characteristic preference information of this user can record imperial palace subject matter game; Some users like the game of fighting of racing, then the game fight mode preference information of this user can record sports fight.These are only citing, in the present invention, user preference information includes but are not limited to above-mentioned specifying information.
Step S201, obtains type of play information, the game characteristic information of multiple game, play life cycle information and game income information by data mining.
In step s 201, the mode such as to get ready by large data analysis, data and carry out data mining, obtain the game datas such as the type of play information of multiple game, game characteristic information, game life cycle information and game income information.
Particularly, game characteristic information comprises: IP attribute information, game fine arts style information, game picture information and game developer's information; Game income information comprises: game real revenue information and game revenue potential information.Wherein, game characteristic information also comprises: game main management information and game user liveness information.According to the game main management information of certain game, can know whether this game is main management game.These are only citing, characteristic information of playing in the present invention includes but are not limited to above-mentioned specifying information with game income information.
Wherein, step S200 and step S201 can perform simultaneously, also can first execution of step S200, then performs step S201.
Step S202, according to user's characteristic information, user preference information, user charges information and user's game records information, determines the user property of each user.
After step S200 obtains the user's characteristic information of multiple user, user preference information, user charges information and user's game records information, step S202, according to these user data, determines the user property of each user.
Step S203, according to user property, generates user's portrait of each user.
After step S202 determines user property, step S203 just according to user property, can generate user's portrait of each user.Wherein, user property can be known exactly by user's portrait.
Step S204, according to type of play information, game characteristic information, game life cycle information and game income information, determines the game attributes of each game.
After step S201 obtains type of play information, the game characteristic information of multiple game, play life cycle information and game income information, step S204, according to these game datas, determines the game attributes of each game.
Step S205, according to game attributes, generates the game portrait of each game.
After step S204 determines game attributes, step S205 just according to game attributes, can generate the game portrait of each game.Wherein, game attributes can be known exactly by game portrait.
Alternatively, step S202, step S203 can perform with step S204, step S205 simultaneously, also can first execution of step S202 and step S203 successively, then perform step S204 and step S205 successively.
Step S206, for one of them user in multiple user, according at least one the coupling index preset, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended, give this user by activity recommendation to be recommended.
Wherein, the activity of game correspondence can comprise the activity of supplementing with money, new hand is movable, the activity that forum's activity etc. are relevant, particularly, draw a portrait to enable user and effectively to mate with portrait of playing, not only pre-set at least one coupling index, but also pre-set corresponding weight for each coupling index, therefore for one of them user in multiple user, according at least one the coupling index preset and the corresponding weight of default each coupling index, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, the activity to be recommended of this user applicable is selected from the activity of the game correspondence of coupling, this user is given by activity recommendation to be recommended.
Such as, in step S206, the game of the coupling obtained for user 1 is game 1, game 2 and game 3.Wherein, the matching degree that the game portrait of game 1, the game portrait of game 2, the game game portrait of 3 and the user of user 1 draw a portrait is successively decreased successively, and the matching degree that the game game portrait of 1 and the user of user 1 draw a portrait is the highest.Then the activity of game 1, game 2 and 3 correspondences of playing is obtained.Suppose, the activity of 1 correspondence of playing comprises: the activity of supplementing with money 11, the activity of supplementing with money 12, the activity of supplementing with money 13, new hand's activity 11, new hand movable 12 and forum's activity 11, wherein, the activity of the activity of supplementing with money 11 for supplementing 10 yuan with money, the activity of the activity of supplementing with money 12 for supplementing 50 yuan with money, the activity of the activity of supplementing with money 13 for supplementing 100 yuan with money; The activity of 2 correspondences of playing comprises: the activity of supplementing with money 21, the activity of supplementing with money 22, new hand's activity 21, new hand movable 22 and forum's activity 21, wherein, and the activity of the activity of supplementing with money 21 for supplementing 10 yuan with money, the activity of the activity of supplementing with money 22 for supplementing 100 yuan with money; The activity of 3 correspondences of playing comprises: the activity of supplementing with money 31, the activity of supplementing with money 32, new hand movable 31 and new hand's activity 32.Then draw a portrait known according to the user of user 1, user 1 take part in game 1 and game ratings is higher, and user 1 once repeatedly filled value for game 1 and had higher paying potentiality, but user 1 has just participated in game 2 and game ratings is lower, and user 1 did not fill value for game 2, in addition, user 1 not yet participates in game 3, then draw a portrait according to the user of user 1, for the selected activity to be recommended of taking out of game 1 for supplementing movable 12 with money, supplement movable 13 and forum's activity 11 with money, for the selected activity to be recommended of taking out of game 2 for supplementing movable 21 with money, new hand's activity 21, new hand movable 22 and forum's activity 21, activity to be recommended for the selected taking-up of game 3 is new hand's activity 31, so, when user 1 opens gaming platform or game webpage, the method utilizes gaming platform or game webpage by the activity of supplementing with money 12 of game 1, supplement movable 13 with money, forum's activity 11, the activity of supplementing with money 21 of game 2, new hand's activity 21, new hand's activity 22, user 1 is recommended in new hand's activity 31 of forum movable 21 and game 3.Therefore, the travelling activity recommended to user 1 is all that user 1 may more interested ludic activity, cause dislike therefore can not to user 1, improve Consumer's Experience sense.
According to the ludic activity recommend method that the present embodiment provides, the user data of multiple user and the game data of multiple game is obtained by data mining, then user's portrait of each user and the game portrait of each game is generated according to user data and game data respectively, last for one of them user in multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, the activity to be recommended of this user applicable is selected from the activity of the game correspondence of coupling, this user is given by activity recommendation to be recommended.User's portrait mates with game portrait by technical scheme provided by the invention, obtain the game of the coupling of certain user applicable, then from the activity of the game correspondence of coupling, select the activity to be recommended of this user applicable, this user is given by activity recommendation to be recommended, thus achieve the intelligent recommendation of ludic activity, improve the recommendation effect of ludic activity, optimize the way of recommendation of ludic activity.
Fig. 3 shows the illustrative view of functional configuration of ludic activity recommendation apparatus according to an embodiment of the invention, as shown in Figure 3, this device comprises: the first acquisition module 301, first generation module 302, second generation module 303, matching module 304, second acquisition module 305 and recommending module 306.
First acquisition module 301 is suitable for: obtain the user data of multiple user and the game data of multiple game by data mining.
First acquisition module 301 mode such as to be got ready by large data analysis, data and is carried out data mining, obtains the user data of multiple user and the game data of multiple game.
First acquisition module 301 is further adapted for: obtain the user's characteristic information of multiple user, user preference information, user charges information and user's game records information by data mining.
Particularly, user's characteristic information comprises: user's inherent feature and user sources channel; User preference information comprises: user browses preference information, user clicks preference information and user's liveness information; User charges information comprises: user charges recorded information and user charges potentiality information; User's game records information comprises: user participates in game information and user's game ratings information.Wherein, user's inherent feature comprises: the features such as user's sex, age of user and user's constellation.In addition, in order to the game of multianalysis user is liked, user preference information also can comprise other preference information
First acquisition module 301 is further adapted for: obtain type of play information, the game characteristic information of multiple game, play life cycle information and game income information by data mining.
Particularly, game characteristic information comprises: IP attribute information, game fine arts style information, game picture information and game developer's information; Game income information comprises: game real revenue information and game revenue potential information.Wherein, game characteristic information also comprises: game main management information and game user liveness information.According to the game main management information of certain game, can know whether this game is main management game.These are only citing, characteristic information of playing in the present invention includes but are not limited to above-mentioned specifying information with game income information.
First generation module 302 is suitable for: the user data obtained according to the first acquisition module 301 generates user's portrait of each user.
After the first acquisition module 301 obtains the user data of multiple user, the first generation module 302 generates user's portrait of each user according to user data.Wherein, user property can be known exactly by user's portrait.
First generation module 302 is further adapted for: the user data obtained according to the first acquisition module 301, determines the user property of each user; According to user property, generate user's portrait of each user.
Second generation module 303 is suitable for: the game data obtained according to the first acquisition module 301 generates the game portrait of each game.
After the first acquisition module 301 obtains the game data of multiple game, the second generation module 303 generates the game portrait of each game according to game data.Wherein, game attributes can be known exactly by game portrait.
Second generation module 303 is further adapted for: the game data obtained according to the first acquisition module 301, determines the game attributes of each game; According to game attributes, generate the game portrait of each game.
Matching module 304 is suitable for: for one of them user in multiple user, mating, obtaining the game of mating by being drawn a portrait with the game of multiple game by the user of this user portrait.
Second acquisition module 305 is suitable for: for one of them user in multiple user, obtains the activity of the game correspondence of coupling.
Wherein, the relevant activity such as the activity that game is corresponding can comprise the activity of supplementing with money, new hand is movable, forum is movable.
Recommending module 306, is suitable for for one of them user in multiple user, and the activity recommendation of the game correspondence of the coupling obtained by the second acquisition module 305 gives this user.
Matching module 304 is further adapted for: for one of them user in multiple user, according at least one the coupling index preset, is drawn a portrait by the user of this user portrait and mates, obtain the game of mating with the game of multiple game.
Particularly, draw a portrait to enable user and effectively to mate with portrait of playing, not only pre-set at least one coupling index, but also pre-set corresponding weight for each coupling index, therefore matching module 304 is further adapted for: for one of them user in multiple user, according at least one the coupling index preset and the corresponding weight of default each coupling index, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating.
Second acquisition module 305 is further adapted for: for one of them user in multiple user, obtains the activity of the game correspondence of coupling, and draws a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended.
Recommending module 306 is further adapted for: for one of them user in multiple user, and the activity recommendation to be recommended obtained by the second acquisition module 305 gives this user.
Second acquisition module 305 is for one of them user in multiple user, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select the activity to be recommended of this user applicable, then the activity recommendation to be recommended that obtained by second acquisition module 305 of recommending module 306 is to this user.
According to the ludic activity recommendation apparatus that the present embodiment provides, first acquisition module obtains the user data of multiple user and the game data of multiple game by data mining, then the first generation module and the second generation module generate user's portrait of each user and the game portrait of each game according to user data and game data respectively, last matching module is for one of them user in multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, second acquisition module obtains the activity of the game correspondence of coupling, the activity recommendation of the game correspondence of coupling is given this user by recommending module.User's portrait mates with game portrait by technical scheme provided by the invention, obtain the game of the coupling of certain user applicable, this user is given by the activity recommendation of the game correspondence of coupling, thus achieve the intelligent recommendation of ludic activity, improve the recommendation effect of ludic activity, optimize the way of recommendation of ludic activity.
Intrinsic not relevant to any certain computer, virtual system or miscellaneous equipment with display at this algorithm provided.Various general-purpose system also can with use based on together with this teaching.According to description above, the structure constructed required by this type systematic is apparent.In addition, the present invention is not also for any certain programmed language.It should be understood that and various programming language can be utilized to realize content of the present invention described here, and the description done language-specific is above to disclose preferred forms of the present invention.
In description provided herein, describe a large amount of detail.But can understand, embodiments of the invention can be put into practice when not having these details.In some instances, be not shown specifically known method, structure and technology, so that not fuzzy understanding of this description.
Similarly, be to be understood that, in order to simplify the disclosure and to help to understand in each inventive aspect one or more, in the description above to exemplary embodiment of the present invention, each feature of the present invention is grouped together in single embodiment, figure or the description to it sometimes.But, the method for the disclosure should be construed to the following intention of reflection: namely the present invention for required protection requires feature more more than the feature clearly recorded in each claim.Or rather, as claims below reflect, all features of disclosed single embodiment before inventive aspect is to be less than.Therefore, the claims following detailed description of the invention are incorporated to this detailed description of the invention thus clearly, and wherein each claim itself is as independent embodiment of the present invention.
Those skilled in the art are appreciated that and adaptively can change the module in the equipment in embodiment and they are arranged in one or more equipment different from this embodiment.Module in embodiment or unit or assembly can be combined into a module or unit or assembly, and multiple submodule or subelement or sub-component can be put them in addition.Except at least some in such feature and/or process or unit be mutually repel except, any combination can be adopted to combine all processes of all features disclosed in this description (comprising adjoint claim, summary and accompanying drawing) and so disclosed any method or equipment or unit.Unless expressly stated otherwise, each feature disclosed in this description (comprising adjoint claim, summary and accompanying drawing) can by providing identical, alternative features that is equivalent or similar object replaces.
In addition, those skilled in the art can understand, although embodiments more described herein to comprise in other embodiment some included feature instead of further feature, the combination of the feature of different embodiment means and to be within scope of the present invention and to form different embodiments.Such as, in the following claims, the one of any of embodiment required for protection can use with arbitrary combination.
All parts embodiment of the present invention with hardware implementing, or can realize with the software module run on one or more processor, or realizes with their combination.It will be understood by those of skill in the art that the some or all functions that microprocessor or digital signal processor (DSP) can be used in practice to realize according to the some or all parts in the embodiment of the present invention.The present invention can also be embodied as part or all equipment for performing method as described herein or device program (such as, computer program and computer program).Realizing program of the present invention and can store on a computer-readable medium like this, or the form of one or more signal can be had.Such signal can be downloaded from internet website and obtain, or provides on carrier signal, or provides with any other form.
The present invention will be described instead of limit the invention to it should be noted above-described embodiment, and those skilled in the art can design alternative embodiment when not departing from the scope of claims.In the claims, any reference symbol between bracket should be configured to limitations on claims.Word " comprises " not to be got rid of existence and does not arrange element in the claims or step.Word "a" or "an" before being positioned at element is not got rid of and be there is multiple such element.The present invention can by means of including the hardware of some different elements and realizing by means of the computer of suitably programming.In the unit claim listing some devices, several in these devices can be carry out imbody by same hardware branch.Word first, second and third-class use do not represent any order.Can be title by these word explanations.
The invention discloses:
A1, a kind of ludic activity recommend method, comprising:
The user data of multiple user and the game data of multiple game is obtained by data mining;
User's portrait of each user is generated according to described user data;
The game portrait of each game is generated according to described game data;
For one of them user in described multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, give this user by the activity recommendation of the game correspondence of coupling.
A2, method according to A1, for one of them user in described multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, comprise to this user further the activity recommendation of the game correspondence of coupling:
For one of them user in described multiple user, according at least one the coupling index preset, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended, give this user by activity recommendation to be recommended.
A3, method according to A2, for one of them user in described multiple user, according at least one the coupling index preset, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended, comprise to this user further activity recommendation to be recommended:
For one of them user in described multiple user, according at least one the coupling index preset and the corresponding weight of default each coupling index, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended, give this user by activity recommendation to be recommended.
A4, method according to any one of A1-A3, the user data being obtained multiple user by data mining is comprised further: obtain the user's characteristic information of multiple user, user preference information, user charges information and user's game records information by data mining.
A5, method according to A4, described user's characteristic information comprises: user's inherent feature and user sources channel;
Described user preference information comprises: user browses preference information, user clicks preference information and user's liveness information;
Described user charges information comprises: user charges recorded information and user charges potentiality information;
Described user's game records information comprises: user participates in game information and user's game ratings information.
A6, method according to any one of A1-A5, the game data being obtained multiple game by data mining is comprised further: obtain the type of play information of multiple game, game characteristic information, game life cycle information and game income information by data mining.
A7, method according to A6, described game characteristic information comprises: IP attribute information, game fine arts style information, game picture information and game developer's information;
Game income information comprises: game real revenue information and game revenue potential information.
A8, method according to any one of A1-A7, the described user's portrait generating each user according to described user data comprises further:
According to described user data, determine the user property of each user;
According to described user property, generate user's portrait of each user.
A9, method according to any one of A1-A8, the described game portrait generating each game according to described game data comprises further:
According to described game data, determine the game attributes of each game;
According to described game attributes, generate the game portrait of each game.
B10, a kind of ludic activity recommendation apparatus, comprising:
First acquisition module, is suitable for obtaining the user data of multiple user and the game data of multiple game by data mining;
First generation module, the user data being suitable for obtaining according to described first acquisition module generates user's portrait of each user;
Second generation module, the game data being suitable for obtaining according to described first acquisition module generates the game portrait of each game;
Matching module, is suitable for for one of them user in described multiple user, mating, obtaining the game of mating by being drawn a portrait with the game of multiple game by the user of this user portrait;
Second acquisition module, is suitable for for one of them user in described multiple user, obtains the activity of the game correspondence of coupling;
Recommending module, is suitable for for one of them user in described multiple user, and the activity recommendation of the game correspondence of the coupling obtained by described second acquisition module gives this user.
B11, device according to B10, described matching module is further adapted for: for one of them user in described multiple user, according at least one the coupling index preset, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating;
Described second acquisition module is further adapted for: for one of them user in described multiple user, obtains the activity of the game correspondence of coupling, and draws a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended;
Described recommending module is further adapted for: for one of them user in described multiple user, and the activity recommendation to be recommended obtained by described second acquisition module gives this user.
B12, device according to B11, described matching module is further adapted for: for one of them user in described multiple user, according at least one the coupling index preset and the corresponding weight of default each coupling index, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating.
B13, device according to any one of B10-B12, described first acquisition module is further adapted for: obtain the user's characteristic information of multiple user, user preference information, user charges information and user's game records information by data mining.
B14, device according to B13, described user's characteristic information comprises: user's inherent feature and user sources channel;
Described user preference information comprises: user browses preference information, user clicks preference information and user's liveness information;
Described user charges information comprises: user charges recorded information and user charges potentiality information;
Described user's game records information comprises: user participates in game information and user's game ratings information.
B15, device according to any one of B10-B14, described first acquisition module is further adapted for: obtain the type of play information of multiple game, game characteristic information, game life cycle information and game income information by data mining.
B16, device according to B15, described game characteristic information comprises: IP attribute information, game fine arts style information, game picture information and game developer's information;
Game income information comprises: game real revenue information and game revenue potential information.
B17, device according to any one of B10-B16, described first generation module is further adapted for:
According to the user data that described first acquisition module obtains, determine the user property of each user;
According to described user property, generate user's portrait of each user.
B18, device according to any one of B10-B17, described second generation module is further adapted for:
According to the game data that described first acquisition module obtains, determine the game attributes of each game;
According to described game attributes, generate the game portrait of each game.
Claims (10)
1. a ludic activity recommend method, comprising:
The user data of multiple user and the game data of multiple game is obtained by data mining;
User's portrait of each user is generated according to described user data;
The game portrait of each game is generated according to described game data;
For one of them user in described multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, give this user by the activity recommendation of the game correspondence of coupling.
2. method according to claim 1, for one of them user in described multiple user, mate by the user of this user portrait is drawn a portrait with the game of multiple game, obtain the game of mating, and obtain the activity of the game correspondence of coupling, comprise to this user further the activity recommendation of the game correspondence of coupling:
For one of them user in described multiple user, according at least one the coupling index preset, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended, give this user by activity recommendation to be recommended.
3. method according to claim 2, for one of them user in described multiple user, according at least one the coupling index preset, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended, comprise to this user further activity recommendation to be recommended:
For one of them user in described multiple user, according at least one the coupling index preset and the corresponding weight of default each coupling index, the user of this user portrait is drawn a portrait with the game of multiple game and mates, obtain the game of mating, obtain the activity of the game correspondence of coupling, and draw a portrait according to the user of this user, from the activity of the game correspondence of coupling, select activity to be recommended, give this user by activity recommendation to be recommended.
4. the method according to any one of claim 1-3, the user data being obtained multiple user by data mining is comprised further: obtain the user's characteristic information of multiple user, user preference information, user charges information and user's game records information by data mining.
5. method according to claim 4, described user's characteristic information comprises: user's inherent feature and user sources channel;
Described user preference information comprises: user browses preference information, user clicks preference information and user's liveness information;
Described user charges information comprises: user charges recorded information and user charges potentiality information;
Described user's game records information comprises: user participates in game information and user's game ratings information.
6. the method according to any one of claim 1-5, the game data being obtained multiple game by data mining is comprised further: obtain type of play information, the game characteristic information of multiple game, play life cycle information and game income information by data mining.
7. method according to claim 6, described game characteristic information comprises: IP attribute information, game fine arts style information, game picture information and game developer's information;
Game income information comprises: game real revenue information and game revenue potential information.
8. the method according to any one of claim 1-7, described according to described user data generate each user user portrait comprise further:
According to described user data, determine the user property of each user;
According to described user property, generate user's portrait of each user.
9. the method according to any one of claim 1-8, described according to described game data generate each game game portrait comprise further:
According to described game data, determine the game attributes of each game;
According to described game attributes, generate the game portrait of each game.
10. a ludic activity recommendation apparatus, comprising:
First acquisition module, is suitable for obtaining the user data of multiple user and the game data of multiple game by data mining;
First generation module, the user data being suitable for obtaining according to described first acquisition module generates user's portrait of each user;
Second generation module, the game data being suitable for obtaining according to described first acquisition module generates the game portrait of each game;
Matching module, is suitable for for one of them user in described multiple user, mating, obtaining the game of mating by being drawn a portrait with the game of multiple game by the user of this user portrait;
Second acquisition module, is suitable for for one of them user in described multiple user, obtains the activity of the game correspondence of coupling;
Recommending module, is suitable for for one of them user in described multiple user, and the activity recommendation of the game correspondence of the coupling obtained by described second acquisition module gives this user.
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