CN105786885A - Message notification generation method and system, and electronic equipment - Google Patents
Message notification generation method and system, and electronic equipment Download PDFInfo
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Abstract
The invention discloses a message notification generation method. The method comprises the following steps: acquiring attribute information of a first data object, wherein the attribute information comprises at least one of three types of information of the first data object, i.e., login information, recharge times information, and recharge amount data information, and the first data object is a data object newly added within a set time interval; calling a pre-established prediction data model for analysis of the attribute information of the first data object, and obtaining analysis results, wherein the prediction data model is generated according to historical login information, historical recharge times information and historical recharge amount data information of data objects that satisfy set conditions; determining whether the first data object belongs to type I data objects or type II data objects according to the analysis results, wherein the type I data objects are data objects satisfying a first set rule, and the type II data objects are data objects satisfying a second set rule; and generating a message notification corresponding to the type of the first data object according to the type of the first data object.
Description
Technical field
The present invention relates to field of computer technology, be specifically related to the generation method and system of a kind of message informing and a kind of electronic equipment.
Background technology
Along with the development of computer technology, the number of applications of each terminal platform grows with each passing day, and increasing enterprise hankers after using powerful management class platform (software) that each user object is managed.
But, in actual applications, the substantial amounts of the user object owing to manage, often occur managing problems such as omitting, repeat, the efficiency of management is low, and the problem that user object runs off often occurs.Visible, those skilled in the art need the problem of solution is how to improve the efficiency of management badly, the relation chain of stable and extending user object, it is prevented that user object loss.
Summary of the invention
In view of the above problems, it is proposed that the present invention is to provide a kind of and overcome the problems referred to above or solve the generation method and system of a kind of message informing of the problems referred to above and a kind of electronic equipment at least in part.
According to one aspect of the present invention, it is provided that a kind of generation method of message informing, including:
Obtain the attribute information of the first data object；Wherein, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval；
Call the pre-established prediction data model attribute information to described first data object to be analyzed, obtain analyzing result；Wherein, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates；
According to described analysis result, it is determined that described first data object is primary sources object or secondary sources object；Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule；
Classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
According to another aspect of the present invention, it is provided that the generation system of a kind of message informing, including:
First acquisition module, for obtaining the attribute information of the first data object；Wherein, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval；
Analysis module, is analyzed for calling the pre-established prediction data model attribute information to described first data object, obtains analyzing result；Wherein, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates；
Module is determined in classification, for according to described analysis result, it is determined that described first data object is primary sources object or secondary sources object；Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule；
Message generating module, for the classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
Correspondingly, the invention also discloses a kind of electronic equipment, including the generation system of message informing as above.
The generation scheme of a kind of message informing disclosed in the embodiment of the present invention, it is analyzed processing to the attribute information of the first data object by pre-established prediction data model, determine the classification of described first data object, finally according to the message informing of the classification generation object of the first data object.First data object can be managed targetedly by the management personnel being responsible for described first data object according to the prompting of described message informing, stablizes in time or sets up the relation chain between data object, improves user's stickiness, it is to avoid customer loss.
Further, the analysis result Auto-matching of attribute information is generated by described message informing according to prediction data model, it is to avoid the manual screening of management personnel, distinguish operation, improves efficiency and the accuracy of management, decreases operating procedure invalid, tediously long.
A kind of data processing scheme based on message content disclosed in the embodiment of the present invention, by the Analysis and Screening to Message Record, determines task performance with this, and then determines data processing rule, finally complete the calculating of target data.Message content is processed with data and is effectively combined, simplify flow chart of data processing, improve data-handling efficiency；And, process the target data result obtained and have more purposiveness and specific aim, practical requirement.
Further, different message contents can be automatically matched to the data processing rule of correspondence, and then adopts the data processing rule of coupling to process data, obtains target data result.Multistage message content can use the data processing rule of correspondence asynchronous to process, and further increases data-handling efficiency.Meanwhile, by the regular process data of multiple data processing rule, it is to avoid data processing step tediously long, decrease invalidation step, reduce platform and run burden.
Described above is only the general introduction of technical solution of the present invention, in order to better understand the technological means of the present invention, and can be practiced according to the content of description, and in order to above and other objects of the present invention, feature and advantage can be become apparent, below especially exemplified by the specific embodiment of the present invention.
Accompanying drawing explanation
By reading hereafter detailed description of the preferred embodiment, various other advantage and benefit those of ordinary skill in the art be will be clear from understanding.Accompanying drawing is only for illustrating the purpose of preferred implementation, and is not considered as limitation of the present invention.And in whole accompanying drawing, it is denoted by the same reference numerals identical parts.In the accompanying drawings:
Fig. 1 is the flow chart of steps of the generation method of a kind of message informing in the embodiment of the present invention one；
Fig. 2 is the flow chart of steps of the generation method of a kind of message informing in the embodiment of the present invention two；
Fig. 3 is the flow chart of steps of the generation method of a kind of message informing in the embodiment of the present invention three；
Fig. 4 is the structured flowchart of the generation system of a kind of message informing in the embodiment of the present invention four；
Fig. 5 is the structured flowchart of the generation system of a kind of message informing in the embodiment of the present invention five.
Detailed description of the invention
It is more fully described the exemplary embodiment of the disclosure below with reference to accompanying drawings.Although accompanying drawing showing the exemplary embodiment of the disclosure, it being understood, however, that may be realized in various forms the disclosure and should do not limited by embodiments set forth here.On the contrary, it is provided that these embodiments are able to be best understood from the disclosure, and complete for the scope of the present disclosure can be conveyed to those skilled in the art.
Embodiment one
With reference to Fig. 1, it is shown that the flow chart of steps of a kind of generation method of message informing in the embodiment of the present invention one.In the present embodiment, the generation method of described message informing includes:
Step 102, obtains the attribute information of the first data object.
In the present embodiment, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message.Wherein, described first data object is at the newly-increased data object set in time interval.If the user object that will first log in 24 hours before current time is as the first data object.
Step 104, calls the pre-established prediction data model attribute information to described first data object and is analyzed, and obtains analyzing result.
In the present embodiment, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates.Wherein, described historical log information, history supplement number information with money and history recharge amount data message corresponds respectively to the log-on message in the attribute information of described first data object, supplements number information and recharge amount data message with money.
Step 106, according to described analysis result, it is determined that described first data object is primary sources object or secondary sources object.
In the present embodiment, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule.
Step 108, the classification according to described first data object, generate the message informing of the classification corresponding to described first data object.
It is preferred that if it is determined that described first data object is primary sources object, then generate the first message informing of correspondence.If it is determined that described first data object is secondary sources object, then generate the second message informing of correspondence.
In sum, the generation method of a kind of message informing disclosed in the present embodiment, it is analyzed processing to the attribute information of the first data object by pre-established prediction data model, it is determined that the classification of described first data object, finally according to the message informing of the classification generation object of the first data object.First data object can be managed targetedly by the management personnel being responsible for described first data object according to the prompting of described message informing, stablizes in time or sets up the relation chain between data object, improves user's stickiness, it is to avoid customer loss.
Further, the analysis result Auto-matching of attribute information is generated by described message informing according to prediction data model, it is to avoid the manual screening of management personnel, distinguish operation, improves efficiency and the accuracy of management, decreases operating procedure invalid, tediously long.
Embodiment two
With reference to Fig. 2, it is shown that the flow chart of steps of a kind of generation method of message informing in the embodiment of the present invention two.In the present embodiment, the generation method of described message informing includes:
Step 202, generates described prediction data model.
It is preferred that described step 202, including:
Sub-step 2022, obtain described meet the historical log information of data object that imposes a condition, history supplements number information and history recharge amount data message with money.
In the present embodiment, the described satisfied historical data object that data object has been target setting data imposed a condition.Wherein, described target setting data are set, according to described first, the accumulation recharge amount data that rule is determined.
Sub-step 2024, by described historical log information, history supplements number information with money and history recharge amount data message makes correlation analysis with described target setting data respectively, obtains relevance score.
Sub-step 2026, is trained according to multiple relevance score meeting the data object imposed a condition corresponding, obtains described prediction data model.
Needing exist for illustrating, described step 202 is pre-treatment step, in the present embodiment, the generation method of described message informing, also include:
Step 204, obtains the attribute information of the first data object.
In the present embodiment, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message.Wherein, described first data object is at the newly-increased data object set in time interval.
It is preferred that described log-on message includes: login times and/or login time continuously.Described number information of supplementing with money includes: completed in the first setting cycle supplements number of times with money, supplement the frequency of failure, continuous successful recharging number of times and at least one supplemented with money continuously in the frequency of failure with money in the second setting cycle.Recharge amount data message includes: the every time at least one in total recharge amount data of recharge amount data, average recharge amount data in the 3rd setting cycle and accumulation.
Step 206, calls the pre-established prediction data model attribute information to described first data object and is analyzed, and obtains analyzing result.
In the present embodiment, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates.
It is preferred that described step 206, including:
Sub-step 2062, is analyzed comparing to the log-on message of described first data object by described prediction data model, obtains the first comparative result；And/or,
Sub-step 2064, is analyzed comparing to the number information of supplementing with money of described first data object by described prediction data model, obtains the second comparative result；And/or,
Sub-step 2066, is analyzed comparing to the recharge amount data message of described first data object by described prediction data model, obtains the 3rd comparative result；
Sub-step 2068, according to the first comparative result obtained and/or the second comparative result and/or the 3rd comparative result, it is determined that described analysis result.
Step 208, according to described analysis result, it is determined that described first data object is primary sources object or secondary sources object.
In the present embodiment, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule.Wherein, described first set rule and set threshold value be more than or equal to first as: accumulation recharge amount data；Described second sets rule sets threshold value as: accumulation recharge amount data less than or equal to second.Described first sets threshold value sets threshold value be more than or equal to described second.
Step 210, the classification according to described first data object, generate the message informing of the classification corresponding to described first data object.
In the present embodiment, if described first data object is primary sources object, then generate recommendation message notice, to point out described first data object for recommending data object.If described first data object is secondary sources object, then generate alarm information notice, to point out described first data object for risk data object.
In sum, the generation method of a kind of message informing disclosed in the present embodiment, it is analyzed processing to the attribute information of the first data object by pre-established prediction data model, it is determined that the classification of described first data object, finally according to the message informing of the classification generation object of the first data object.First data object can be managed targetedly by the management personnel being responsible for described first data object according to the prompting of described message informing, stablizes in time or sets up the relation chain between data object, improves user's stickiness, it is to avoid customer loss.
Further, the analysis result Auto-matching of attribute information is generated by described message informing according to prediction data model, it is to avoid the manual screening of management personnel, distinguish operation, improves efficiency and the accuracy of management, decreases operating procedure invalid, tediously long.
Embodiment three
In conjunction with above-described embodiment, a kind of generation method of message informing, for the flow process generating message informing in based on the game management system platform of web page, is described in detail by the present embodiment.
In the present embodiment, a kind of game management system platform realized based on browser web page includes multiple member, member is divided into multiple rank according to administration authority, as: manager's rank, supervisor's rank and assistant director's rank, manager is responsible for the supervisor and/or assistant director that are under the jurisdiction of under its department, and supervisor is responsible for the assistant director being under the jurisdiction of under its department.Game player's object is managed by described member by described game management system platform.The attribute information of described game player's object all records and is saved in described game management system platform side.
It is preferred that described game player's object can be divided into new game player's object and old game player's object according to setting time interval.
As, using the 00:00-24:00 on January 1st, 2014 as described setting time interval, if game player's object first logs into a game in this setting time interval, then this game player's object is new game player's object, using described new game player's object as the first data object.
If game player's object had the record of logging in game before this setting time interval, then this game player's object is old game player's object, using described old game player's object as historical data object.Further, if the recharge amount data of described historical data object meet target setting data, then using described second data object as meeting the data object imposed a condition.That is, meet the historical data object that data object has been target setting data imposed a condition.
With reference to Fig. 3, it is shown that the flow chart of steps of a kind of generation method of message informing in the embodiment of the present invention three.In the present embodiment, the generation method of described message informing includes following pre-treatment step,
Pre-treatment step 302, generates described prediction data model.
It is preferred that described pre-treatment step 302 specifically includes:
Sub-step 3022, obtain described meet the historical log information of data object that imposes a condition, history supplements number information and history recharge amount data message with money
Sub-step 3024, by described historical log information, history supplements number information with money and history recharge amount data message makes correlation analysis with described target setting data respectively, obtains relevance score.
In the present embodiment, described target setting data are set, according to described first, the accumulation recharge amount data that rule is determined.Wherein, described first set rule and set threshold value be more than or equal to first as: accumulation recharge amount data.Such as, if described first sets threshold value as $10000, then described target setting data are 10000.
Sub-step 3026, is trained according to multiple relevance score meeting the data object imposed a condition corresponding, obtains described prediction data model.
In the present embodiment, described method also includes:
Step 304, obtains the attribute information of the first data object.
In the present embodiment, e.g., game player's object A and game player object B is new game player's object, i.e. the first data object.Then, the attribute information of game player object A and game player object B is obtained respectively.Wherein, the attribute information of game player object A is: logs in continuously 5 game in seven days, supplemented with money 3 times in seven days, in seven days accumulation recharge amount data data $1000；The attribute information of game player object B is: logs in continuously 1 game in seven days, supplemented with money 0 time in seven days, in seven days accumulation recharge amount data data $0.
Step 306, calls described prediction data model and respectively the attribute information of game player object A and game player object B is analyzed.
In the present embodiment, following information can be obtained according to described prediction data model: meet the data object that imposes a condition in seven days the average time of continuous logging in game more than 3, on average supplement with money number of times more than 2, accumulation recharge amount is more than 900.
As can be seen here, by prediction data model, the attribute information of described game player object A is analyzed, it may be determined that described game player object A is primary sources object, and game player object B is secondary sources object.Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule.It is preferred that described first sets rule and sets threshold value (foregoing 10000, namely described target setting data) be more than or equal to first as: accumulation recharge amount data；Described second sets rule sets threshold value as: accumulation recharge amount data less than or equal to second, and wherein, described second to set threshold value can be 10000, or the arbitrary value less than 10000.
Step 308, generates recommendation message notice, to point out described game player object A for recommending data object；And, generate alarm information notice, to point out described game player object B for risk data object.
In the present embodiment, the recommendation message of generation notifies and alarm information notice is described based on all or part member side under the game management system platform of web by being sent to, and carries out managing targetedly, servicing to game player object A and game player object B for the member under described game management system platform.
In sum, the generation method of a kind of message informing disclosed in the present embodiment, it is analyzed processing to the attribute information of the first data object by pre-established prediction data model, it is determined that the classification of described first data object, finally according to the message informing of the classification generation object of the first data object.First data object can be managed targetedly by the management personnel being responsible for described first data object according to the prompting of described message informing, stablizes in time or sets up the relation chain between data object, improves user's stickiness, it is to avoid customer loss.
Further, the analysis result Auto-matching of attribute information is generated by described message informing according to prediction data model, it is to avoid the manual screening of management personnel, distinguish operation, improves efficiency and the accuracy of management, decreases operating procedure invalid, tediously long.
It should be noted that, for aforesaid embodiment of the method, in order to be briefly described, therefore it is all expressed as a series of combination of actions, but those skilled in the art should know, the present invention is not by the restriction of described sequence of movement, because according to the present invention, some step can adopt other orders or carry out simultaneously.Secondly, those skilled in the art also should know, embodiment described in this description belongs to preferred embodiment, and involved action is not necessarily essential to the invention.
Embodiment four
Based on inventive concept same as said method embodiment.With reference to Fig. 4, it is shown that the structured flowchart of the generation system of a kind of message informing in the embodiment of the present invention four.In the present embodiment, the generation system of described message informing includes:
First acquisition module 402, for obtaining the attribute information of the first data object.
Wherein, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval.
Analysis module 404, is analyzed for calling the pre-established prediction data model attribute information to described first data object, obtains analyzing result.
Wherein, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates.
Module 406 is determined in classification, for according to described analysis result, it is determined that described first data object is primary sources object or secondary sources object.
Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule.
Message generating module 408, for the classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
In sum, the generation system of a kind of message informing disclosed in the present embodiment, it is analyzed processing to the attribute information of the first data object by pre-established prediction data model, it is determined that the classification of described first data object, finally according to the message informing of the classification generation object of the first data object.First data object can be managed targetedly by the management personnel being responsible for described first data object according to the prompting of described message informing, stablizes in time or sets up the relation chain between data object, improves user's stickiness, it is to avoid customer loss.
Further, the analysis result Auto-matching of attribute information is generated by described message informing according to prediction data model, it is to avoid the manual screening of management personnel, distinguish operation, improves efficiency and the accuracy of management, decreases operating procedure invalid, tediously long.
Embodiment five
With reference to Fig. 5, it is shown that the structured flowchart of the generation system of a kind of message informing in the embodiment of the present invention five.In the present embodiment, the generation system of described message informing includes:
Generation module 502, is used for generating described prediction data model.
It is preferred that described generation module 502, including:
Second acquisition module 5022, for obtain described meet the historical log information of data object that imposes a condition, history supplements number information and history recharge amount data message with money.
In the present embodiment, the described satisfied historical data object that data object has been target setting data imposed a condition.Wherein, described target setting data are set, according to described first, the accumulation recharge amount data that rule is determined.
Correlation calculations module 5024, for by described historical log information, history supplements number information with money and history recharge amount data message makes correlation analysis with described target setting data respectively, obtains relevance score.
Training module 5026, for being trained according to multiple relevance score meeting the data object imposed a condition corresponding, obtains described prediction data model.
First acquisition module 504, for obtaining the attribute information of the first data object.
In the present embodiment, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval.
Wherein,
Described log-on message includes: login times and/or login time continuously.
Described number information of supplementing with money includes: completed in the first setting cycle supplements number of times with money, supplement the frequency of failure, continuous successful recharging number of times and at least one supplemented with money continuously in the frequency of failure with money in the second setting cycle.
Recharge amount data message includes: the every time at least one in total recharge amount data of recharge amount data, average recharge amount data in the 3rd setting cycle and accumulation.
Analysis module 506, is analyzed for calling the pre-established prediction data model attribute information to described first data object, obtains analyzing result.
As it was previously stated, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates.
It is preferred that described analysis module 506, including:
First computing module 5062, for being analyzed comparing to the log-on message of described first data object by described prediction data model, obtains the first comparative result.And/or,
Second computing module 5064, for being analyzed comparing to the number information of supplementing with money of described first data object by described prediction data model, obtains the second comparative result.And/or,
3rd computing module 5066, for being analyzed comparing to the recharge amount data message of described first data object by described prediction data model, obtains the 3rd comparative result.
In the present embodiment, it is possible to any one or more by first computing module the 5062, second computing module 5064 and the 3rd computing module 5066, the first comparative result and/or the second comparative result and/or the 3rd comparative result that obtain correspondence are analyzed.
It is preferred that described analysis module 506, also include:
Analyze result and determine module 5068, for according to the first comparative result of obtaining and/or the second comparative result and/or the 3rd comparative result, it is determined that described analysis result.
Module 508 is determined in classification, for according to described analysis result, it is determined that described first data object is primary sources object or secondary sources object.
In the present embodiment, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule.Wherein, described first set rule and set threshold value be more than or equal to first as: accumulation recharge amount data；Described second sets rule sets threshold value as: accumulation recharge amount data less than or equal to second；Described first sets threshold value sets threshold value be more than or equal to described second.
Message generating module 510, for the classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
One it is preferred that described message generating module 510, and specifically for when described first data object is primary sources object, generation recommendation message notice, to point out described first data object for recommending data object.
Another it is preferred that described message generating module 512, specifically for when described first data object is secondary sources object, generation alarm information notice, to point out described first data object for risk data object.
In sum, the generation system of a kind of message informing disclosed in the present embodiment, it is analyzed processing to the attribute information of the first data object by pre-established prediction data model, it is determined that the classification of described first data object, finally according to the message informing of the classification generation object of the first data object.First data object can be managed targetedly by the management personnel being responsible for described first data object according to the prompting of described message informing, stablizes in time or sets up the relation chain between data object, improves user's stickiness, it is to avoid customer loss.
Further, the analysis result Auto-matching of attribute information is generated by described message informing according to prediction data model, it is to avoid the manual screening of management personnel, distinguish operation, improves efficiency and the accuracy of management, decreases operating procedure invalid, tediously long.
Embodiment six
In the present embodiment, provide a kind of electronic equipment, the generation system of the message informing being provided with in above-described embodiment four in this electronic equipment, or, one or more after being provided with in above-described embodiment five in this electronic equipment to the system of embodiment four to have carried out multiple optimization optimize the generation system of message informings.This electronic equipment is for realizing the data processing method based on message content in preceding method embodiment, and has the beneficial effect of corresponding embodiment of the method, does not repeat them here.
For said apparatus embodiment, due to itself and embodiment of the method basic simlarity, so what describe is fairly simple, relevant part illustrates referring to the part of embodiment of the method.
Not intrinsic to any certain computer, virtual system or miscellaneous equipment relevant in algorithm and the display of this offer.Various general-purpose systems can also with use based on together with this teaching.As described above, the structure constructed required by this kind of system is apparent from.Additionally, the present invention is also not for any certain programmed language.It is understood that, it is possible to utilize various programming language to realize the content of invention described herein, and the description above language-specific done is the preferred forms in order to disclose the present invention.
In description mentioned herein, describe a large amount of detail.It is to be appreciated, however, that embodiments of the invention can be put into practice when not having these details.In some instances, known method, structure and technology it are not shown specifically, in order to do not obscure the understanding of this description.
Similarly, it is to be understood that, one or more in order to what simplify that the disclosure helping understands in each inventive aspect, herein above in the description of the exemplary embodiment of the present invention, each feature of the present invention is grouped together in single embodiment, figure or descriptions thereof sometimes.But, the method for the disclosure should be construed to and reflect an intention that namely the present invention for required protection requires feature more more than the feature being expressly recited in each claim.More precisely, as the following claims reflect, inventive aspect is in that all features less than single embodiment disclosed above.Therefore, it then follows claims of detailed description of the invention are thus expressly incorporated in this detailed description of the invention, wherein each claim itself as the independent embodiment of the present invention.
Those skilled in the art are appreciated that, it is possible to carry out the module in the equipment in embodiment adaptively changing and they being 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 excludes each other, it is possible to adopt any combination that all processes or the unit of all features disclosed in this specification (including adjoint claim, summary and accompanying drawing) and so disclosed any method or equipment are combined.Unless expressly stated otherwise, each feature disclosed in this specification (including adjoint claim, summary and accompanying drawing) can be replaced by the alternative features providing purpose identical, equivalent or similar.
In addition, those skilled in the art it will be appreciated that, although embodiments more described herein include some feature included in other embodiments rather than further feature, but the combination of the feature of different embodiment means to be within the scope of the present invention and form different embodiments.Such as, in the following claims, the one of any of embodiment required for protection can mode use in any combination.
The all parts embodiment of the present invention can realize with hardware, or realizes 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 of some or all parts in the generation equipment of the message informing that microprocessor or digital signal processor (DSP) can be used in practice to realize according to embodiments of the present invention.The present invention is also implemented as part or all the equipment for performing method as described herein or device program (such as, computer program and computer program).The program of such present invention of realization can store on a computer-readable medium, or can have the form of one or more signal.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 rather than limits the invention to it should be noted above-described embodiment, and those skilled in the art can design alternative embodiment without departing from the scope of the appended claims.In the claims, any reference marks that should not will be located between bracket is configured to limitations on claims.Word " comprises " and does not exclude the presence of the element or step not arranged in the claims.Word "a" or "an" before being positioned at element does not exclude the presence of multiple such element.The present invention by means of including the hardware of some different elements and can realize by means of properly programmed computer.In the unit claim listing some devices, several in these devices can be through same hardware branch and specifically embody.Word first, second and third use do not indicate that any order.Can be title by these word explanations.
The invention discloses a kind of generation method of A1, message informing, including:
Obtain the attribute information of the first data object；Wherein, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval；
Call the pre-established prediction data model attribute information to described first data object to be analyzed, obtain analyzing result；Wherein, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates；
According to described analysis result, it is determined that described first data object is primary sources object or secondary sources object；Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule；
Classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
A2, method as described in A1, also include: generate described prediction data model.
A3, method as described in A2, the described prediction data model of described generation includes:
Obtain described meet the historical log information of data object that imposes a condition, history supplements number information and history recharge amount data message with money；Wherein, the described satisfied historical data object that data object has been target setting data imposed a condition；
By described historical log information, history supplements number information with money and history recharge amount data message makes correlation analysis with described target setting data respectively, obtains relevance score；
It is trained according to multiple relevance score meeting the data object imposed a condition corresponding, obtains described prediction data model.
A4, method as described in A3, described target setting data are set, according to described first, the accumulation recharge amount data that rule is determined.
A5, method as described in A1, described in call the pre-established prediction data model attribute information to described first data object and be analyzed, obtain analyzing result, including:
It is analyzed comparing to the log-on message of described first data object by described prediction data model, obtains the first comparative result；And/or,
It is analyzed comparing to the number information of supplementing with money of described first data object by described prediction data model, obtains the second comparative result；And/or,
It is analyzed comparing to the recharge amount data message of described first data object by described prediction data model, obtains the 3rd comparative result；
According to the first comparative result obtained and/or the second comparative result and/or the 3rd comparative result, it is determined that described analysis result.
A6, method as described in A1, the described classification according to described first data object, generate the message informing of the classification corresponding to described first data object, including:
If described first data object is primary sources object, then generate recommendation message notice, to point out described first data object for recommending data object.
A7, method as described in A1, the described classification according to described first data object, generate the message informing of the classification corresponding to described first data object, including:
If described first data object is secondary sources object, then generate alarm information notice, to point out described first data object for risk data object.
A8, as arbitrary in A1-A7 as described in method,
Described first sets rule sets threshold value as: accumulation recharge amount data be more than or equal to first；
Described second sets rule sets threshold value as: accumulation recharge amount data less than or equal to second；
Wherein, described first threshold value is set be more than or equal to described second setting threshold value.
A9, as arbitrary in A1-A7 as described in method,
Described log-on message includes: login times and/or login time continuously；
Described number information of supplementing with money includes: completed in the first setting cycle supplements number of times with money, supplement the frequency of failure, continuous successful recharging number of times and at least one supplemented with money continuously in the frequency of failure with money in the second setting cycle；
Recharge amount data message includes: the every time at least one in total recharge amount data of recharge amount data, average recharge amount data in the 3rd setting cycle and accumulation.
The invention also discloses the generation system of B10, a kind of message informing, including:
First acquisition module, for obtaining the attribute information of the first data object；Wherein, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval；
Analysis module, is analyzed for calling the pre-established prediction data model attribute information to described first data object, obtains analyzing result；Wherein, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates；
Module is determined in classification, for according to described analysis result, it is determined that described first data object is primary sources object or secondary sources object；Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule；
Message generating module, for the classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
B11, system as described in B10, also include:
Generation module, is used for generating described prediction data model.
B12, system as described in B11, described generation module, including:
Second acquisition module, for obtain described meet the historical log information of data object that imposes a condition, history supplements number information and history recharge amount data message with money；Wherein, the described satisfied historical data object that data object has been target setting data imposed a condition；
Correlation calculations module, for by described historical log information, history supplements number information with money and history recharge amount data message makes correlation analysis with described target setting data respectively, obtains relevance score；
Training module, for being trained according to multiple relevance score meeting the data object imposed a condition corresponding, obtains described prediction data model.
B13, system as described in B12, described target setting data are set, according to described first, the accumulation recharge amount data that rule is determined.
B14, system as described in B10, described analysis module, including:
First computing module, for being analyzed comparing to the log-on message of described first data object by described prediction data model, obtains the first comparative result；And/or,
Second computing module, for being analyzed comparing to the number information of supplementing with money of described first data object by described prediction data model, obtains the second comparative result；And/or,
3rd computing module, for being analyzed comparing to the recharge amount data message of described first data object by described prediction data model, obtains the 3rd comparative result；
Analyze result and determine module, for according to the first comparative result of obtaining and/or the second comparative result and/or the 3rd comparative result, it is determined that described analysis result.
B15, system as described in B10, described message generating module, specifically for when described first data object is primary sources object, generating recommendation message notice, to point out described first data object for recommending data object.
B16, system as described in B10, described message generating module, specifically for when described first data object is secondary sources object, generating alarm information notice, to point out described first data object for risk data object.
B17, as arbitrary in B10-B16 as described in system,
Described first sets rule sets threshold value as: accumulation recharge amount data be more than or equal to first；
Described second sets rule sets threshold value as: accumulation recharge amount data less than or equal to second；
Wherein, described first threshold value is set be more than or equal to described second setting threshold value.
B18, as arbitrary in B10-B16 as described in system,
Described log-on message includes: login times and/or login time continuously；
Described number information of supplementing with money includes: completed in the first setting cycle supplements number of times with money, supplement the frequency of failure, continuous successful recharging number of times and at least one supplemented with money continuously in the frequency of failure with money in the second setting cycle；
Recharge amount data message includes: the every time at least one in total recharge amount data of recharge amount data, average recharge amount data in the 3rd setting cycle and accumulation.
The invention also discloses C19, a kind of electronic equipment, including the system as described in as arbitrary in B10-B18.
Claims (10)
1. a generation method for message informing, including:
Obtain the attribute information of the first data object；Wherein, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval；
Call the pre-established prediction data model attribute information to described first data object to be analyzed, obtain analyzing result；Wherein, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates；
According to described analysis result, it is determined that described first data object is primary sources object or secondary sources object；Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule；
Classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
2. the method for claim 1, it is characterised in that also include: generate described prediction data model.
3. method as claimed in claim 2, it is characterised in that the described prediction data model of described generation includes:
Obtain described meet the historical log information of data object that imposes a condition, history supplements number information and history recharge amount data message with money；Wherein, the described satisfied historical data object that data object has been target setting data imposed a condition；
By described historical log information, history supplements number information with money and history recharge amount data message makes correlation analysis with described target setting data respectively, obtains relevance score；
It is trained according to multiple relevance score meeting the data object imposed a condition corresponding, obtains described prediction data model.
4. method as claimed in claim 3, it is characterised in that described target setting data are set, according to described first, the accumulation recharge amount data that rule is determined.
5. the method for claim 1, it is characterised in that described in call the pre-established prediction data model attribute information to described first data object and be analyzed, obtain analyzing result, including:
It is analyzed comparing to the log-on message of described first data object by described prediction data model, obtains the first comparative result；And/or,
It is analyzed comparing to the number information of supplementing with money of described first data object by described prediction data model, obtains the second comparative result；And/or,
It is analyzed comparing to the recharge amount data message of described first data object by described prediction data model, obtains the 3rd comparative result；
According to the first comparative result obtained and/or the second comparative result and/or the 3rd comparative result, it is determined that described analysis result.
6. the method for claim 1, it is characterised in that the described classification according to described first data object, generates the message informing of the classification corresponding to described first data object, including:
If described first data object is primary sources object, then generate recommendation message notice, to point out described first data object for recommending data object.
7. the method for claim 1, it is characterised in that the described classification according to described first data object, generates the message informing of the classification corresponding to described first data object, including:
If described first data object is secondary sources object, then generate alarm information notice, to point out described first data object for risk data object.
8. the method as described in claim 1-7 any claim, it is characterised in that
Described first sets rule sets threshold value as: accumulation recharge amount data be more than or equal to first；
Described second sets rule sets threshold value as: accumulation recharge amount data less than or equal to second；
Wherein, described first threshold value is set be more than or equal to described second setting threshold value.
9. a generation system for message informing, including:
First acquisition module, for obtaining the attribute information of the first data object；Wherein, described attribute information includes: the log-on message of described first data object, at least one supplemented with money in number information and recharge amount data message；Described first data object is at the newly-increased data object set in time interval；
Analysis module, is analyzed for calling the pre-established prediction data model attribute information to described first data object, obtains analyzing result；Wherein, described prediction data model according to meeting the historical log information of data object that imposes a condition, history supplements number information with money and history recharge amount data message generates；
Module is determined in classification, for according to described analysis result, it is determined that described first data object is primary sources object or secondary sources object；Wherein, described primary sources object is the data object meeting the first setting rule, and described secondary sources object is the data object meeting the second setting rule；
Message generating module, for the classification according to described first data object, generates the message informing of the classification corresponding to described first data object.
10. an electronic equipment, it is characterised in that include such as right and want the system as described in 9.
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