CN105761110A - Cross-equipment user value analysis method and cross-equipment user value analysis device - Google Patents
Cross-equipment user value analysis method and cross-equipment user value analysis device Download PDFInfo
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Abstract
The invention discloses a cross-equipment user value analysis method and a cross-equipment user value analysis device. The method comprises the steps of acquiring data of a cross-equipment user from at least two pieces of equipment, determining the index set of the cross-equipment user according to the data of the cross-equipment user, adopting a factor analysis approach to determine the characteristic index of the cross-equipment user according to the index set of the cross-equipment user, and evaluating the value of the cross-equipment user according to the characteristic index of the cross-equipment user. Through the method, the value of each cross-equipment user can be analyzed, and the consumption behavior of cross-equipment users is taken into consideration in evaluation of the value of cross-equipment users in addition to the access behavior of cross-equipment users.
Description
Technical field
The present invention relates to technical field of the computer network, in particular to a kind of striding equipment user's Value Engineering Method and device.
Background technology
Along with the development of terminal electronic device is with universal, user's striding equipment accesses the behavior of website to be increased gradually, for instance user uses same subscriber ID to carry out goods browse and/or the operation (user of following so striding equipment operation is referred to as striding equipment user) placed an order on different devices.
Valuation Method for these novel users is different from legacy user, not yet has clear and definite unified definition at present.And more existing striding equipment customer analysis methods, the index added up is excessively general, as browsed the striding equipment number of users of multiple equipment, all having the striding equipment number of users etc. of lower single operation on multiple equipment simultaneously.These indexs are typically only capable to assess the overall striding equipment user of some company (business, product etc.) and are worth, and cannot specific to each striding equipment user.Additionally, existing striding equipment customer analysis method is generally concerned only with the access behavior of striding equipment user, and lack the analysis to its consuming behavior.
Summary of the invention
The present invention provides a kind of striding equipment user's Value Engineering Method and device, it is possible to carries out value analysis for each striding equipment user, and considers navigation patterns and the consuming behavior of striding equipment user when assessing the value of each striding equipment user simultaneously.
Other characteristics of the present invention and advantage will be apparent from by detailed description below, or partially by the practice of the present invention and acquistion.
According to an aspect of the present invention, it is provided that a kind of striding equipment user's Value Engineering Method, including: obtain the data of the striding equipment user coming from least two equipment；Data according to described striding equipment user, it is determined that the index set of described striding equipment user；Index set according to described striding equipment user, adopts factor analysis to determine the characteristic index of described striding equipment user；And the characteristic index according to described striding equipment user, assess the value of described striding equipment user.
According to an embodiment of the present invention, characteristic index according to described striding equipment user, the value assessing described striding equipment user includes: the characteristic index of described striding equipment user is divided into the described respective characteristic index of at least two equipment, and determines the weight that the described respective characteristic index of at least two equipment is corresponding；Weight according to the described respective characteristic index of at least two equipment and correspondence thereof, it is determined that described at least two equipment respective user be worth；And be worth according to the respective user of described at least two equipment, assess the value of described striding equipment user.
According to an embodiment of the present invention, the data according to described striding equipment user, it is determined that the index set of described striding equipment user includes: choose sampling sample from the data of described striding equipment user；And the sampling sample according to described striding equipment user, it is determined that the index set of described striding equipment user.
According to an embodiment of the present invention, described sampling sample is the selected sampling sample taken out from different sample time sections.
According to an embodiment of the present invention, sampling sample according to described striding equipment user, determine that the index set of described striding equipment user includes: the sampling sample according to described striding equipment user, adopt clustering methodology or correlational analysis method, it is determined that the index set of described striding equipment user.
According to an embodiment of the present invention, the index set according to described striding equipment user, adopt factor analysis to determine that the characteristic index of described striding equipment user comprises determining that the explanation degree of factorial analysis；And according to described explanation degree, the index set for described striding equipment user selects multiple factors, and wherein each factor is described index set middle finger target linear combination；Wherein said multiple factor is the characteristic index of described striding equipment user.
According to an embodiment of the present invention, above-mentioned striding equipment user's Value Engineering Method also includes: when evaluating the value of all of described striding equipment user, and each described striding equipment user is classified by the value according to each described striding equipment user；And inhomogeneous described striding equipment user is applied in inhomogeneous business.
According to an embodiment of the present invention, after inhomogeneous described striding equipment user is applied in inhomogeneous business, above-mentioned striding equipment user's Value Engineering Method also includes: according to inhomogeneous described striding equipment user application in corresponding service, check the value assessment result of described striding equipment user.
According to an embodiment of the present invention, the data of described striding equipment user include: the data of described striding equipment user reflection navigation patterns on described at least two equipment and/or the data of reflection purchasing behavior.
According to a further aspect in the invention, it is provided that a kind of striding equipment user's value analysis device, including: user data acquisition module, for obtaining the data of the striding equipment user coming from least two equipment；Index set determines module, the data of the described striding equipment user for obtaining according to described user data acquisition module, it is determined that the index set of described striding equipment user；Characteristic index determines module, for determining the index set of described striding equipment user that module determines according to described index set, adopts factor analysis to determine the characteristic index of described striding equipment user；And user's value assessment module, for determining the characteristic index of described striding equipment user that module determines according to described characteristic index, assess the value of described striding equipment user.
According to an embodiment of the present invention, described user's value assessment module includes: characteristic index classification submodule, characteristic index for described characteristic index is determined described striding equipment user that module determines is divided into the described respective characteristic index of at least two equipment, and determines the weight that the described respective characteristic index of at least two equipment is corresponding；Apparatus value determines submodule, for the weight of the described respective characteristic index of at least two equipment sorted out according to described first characteristic index classification submodule and correspondence thereof, it is determined that described at least two equipment respective user be worth；And value assessment submodule, for determining that the respective user of described at least two equipment that submodule is determined is worth according to described first apparatus value, assess the value of described striding equipment user.
According to an embodiment of the present invention, described index set determines that module includes: sampling submodule, for choosing sampling sample the data of the described striding equipment user obtained from described user data acquisition module；And index determines submodule, the sampling sample of the described striding equipment user for choosing according to described sampling submodule, it is determined that the index set of described striding equipment user.
According to an embodiment of the present invention, the described sampling sample that described sampling submodule is chosen is the selected sampling sample taken out from different sample time sections.
According to an embodiment of the present invention, described index determines that submodule is additionally operable to the sampling sample of the described striding equipment user chosen according to described sampling submodule, adopts clustering methodology or correlational analysis method, it is determined that the index set of described striding equipment user.
According to an embodiment of the present invention, described characteristic index determines that module includes: explanation degree determines submodule, for the explanation degree that certainty factor is analyzed；And selecting predictors submodule, for determining, according to described explanation degree, the described explanation degree that submodule is determined, the index set for described striding equipment user selects multiple factors, and wherein each factor is described index set middle finger target linear combination；Wherein said multiple factor is the characteristic index of described striding equipment user.
According to an embodiment of the present invention, above-mentioned striding equipment user's value analysis device also includes: striding equipment user's sort module, during for going out the value of all of described striding equipment user when described user's value assessment module estimation, value according to each described striding equipment user, classifies to each described striding equipment user；And business application module, for inhomogeneous described striding equipment user is applied in inhomogeneous business.
According to an embodiment of the present invention, above-mentioned striding equipment user's value analysis device also includes: user's inspection of value module, for after inhomogeneous described striding equipment user is applied in inhomogeneous business by described business application module, according to inhomogeneous described striding equipment user application in corresponding service, check the value assessment result of described striding equipment user.
According to an embodiment of the present invention, the data of described striding equipment user include: the data of described striding equipment user reflection navigation patterns on described at least two equipment and/or the data of reflection purchasing behavior.
Striding equipment user's Value Engineering Method according to the present invention, logs in account number according to user, associates user's behavior on different devices, obtains the data on distinct device, and row index of going forward side by side screens；Again through factor analysis, the index filtered out is processed, thus obtaining the characteristic index of striding equipment user；The value of striding equipment user is assessed finally according to characteristic index.The method is possible not only to carry out value analysis for each striding equipment user, and when assessing striding equipment user and being worth, except the access behavior considering striding equipment user, also further contemplates the consuming behavior of striding equipment user.
According to other embodiments, striding equipment user's Value Engineering Method of the present invention, striding equipment user is classified by the value according to each striding equipment user evaluated further；Further according to the business characteristic of all kinds of striding equipment users, it is applied in different business, and adopts different operation ways.The method makes full use of the value of the striding equipment user evaluated, and different striding equipment users is taked different operation ways, optimizes service operation mode, and add Consumer's Experience.
It should be appreciated that above general description and details hereinafter describe and be merely illustrative of, the present invention can not be limited.
Accompanying drawing explanation
Its example embodiment being described in detail by referring to accompanying drawing, above-mentioned and other target of the present invention, feature and advantage will become apparent from.
Fig. 1 is the flow chart of a kind of striding equipment user's Value Engineering Method according to an illustrative embodiments.
Fig. 2 is the flow chart of the another kind of striding equipment user's Value Engineering Method according to an illustrative embodiments.
Fig. 3 is the flow chart of another striding equipment user's Value Engineering Method according to an illustrative embodiments.
Fig. 4 is the block diagram of a kind of striding equipment user's value analysis device according to an illustrative embodiments.
Fig. 5 is the block diagram of the another kind of striding equipment user's value analysis device according to an illustrative embodiments.
Fig. 6 is the block diagram of another striding equipment user's value analysis device according to an illustrative embodiments.
Detailed description of the invention
It is described more fully with example embodiment referring now to accompanying drawing.But, example embodiment can be implemented in a variety of forms, and is not understood as limited to example set forth herein；On the contrary, it is provided that these embodiments make the present invention will more fully and completely, and the design of example embodiment is conveyed to those skilled in the art all sidedly.Accompanying drawing is only the schematic illustrations of the present invention, is not necessarily drawn to scale.Accompanying drawing labelling identical in figure represents same or similar part, thus will omit repetition thereof.
Additionally, described feature, structure or characteristic can be combined in one or more embodiment in any suitable manner.In the following description, it is provided that many details are thus providing fully understanding embodiments of the present invention.It will be appreciated, however, by one skilled in the art that can put into practice technical scheme and omit in described specific detail is one or more, or other method, constituent element, device, step etc. can be adopted.In other cases, known features, method, device, realization or operation are not shown in detail or describe to avoid that a presumptuous guest usurps the role of the host and to make each aspect of the present invention thicken.
Fig. 1 is the flow chart of a kind of striding equipment user's Value Engineering Method according to an illustrative embodiments.As it is shown in figure 1, striding equipment user's Value Engineering Method 10 includes:
In step s 102, the data of the striding equipment user coming from least two equipment are obtained.
Such as, the user registered based on user logs in account number (such as user name, Email or phone number etc.) and striding equipment user behavior at least two equipment (such as PC equipment and the mobile terminal such as smart mobile phone, panel computer) is associated, and obtains the data on the described at least two equipment of this striding equipment user.Data can include data on described at least two equipment, that reflect each index of this striding equipment user browsing behavior and/or (placing an order) behavior of purchase.
Data in step S104, according to this striding equipment user, it is determined that the index set of this striding equipment user.
In order to reflect that striding equipment user is worth comprehensively, the index of the data of acquired this striding equipment user can reflect the value of striding equipment user as much as possible from different perspectives, but among these indexs, some is likely to use not quite, also has some to be likely to be repetition.It is thus desirable to these indexs are screened, so that it is determined that go out the valuable index set that independence is strong, have clear and definite business implication.
In step s 106, the index set according to determined this striding equipment user, adopt factor analysis to determine the characteristic index of this striding equipment user.
The basic object of factor analysis is to go to describe the contact between many indexs by a few factor, the several indexs closer by correlation ratio are returned in same class, each class index just becomes a factor, therefore after Factor Analysis Model is set up, it is possible to go to reflect the most information of former achievement data by fewer several factors.
Adopting factor analysis, the index set for determined this striding equipment user selects the suitable factor, namely the index in index set is sorted out, and wherein each factor is all referring to the linear combination of each index in mark set.When selective factor B, the selected factor need to reach an explanation degree preset, namely to overall explanation degree.This explanation degree can be arranged according to actual needs, for instance can being preset as 80%, the present invention is not limited.
Adopt the factor gone out selected by factor analysis, be the characteristic index of this striding equipment user.
In addition, characteristic index according to this striding equipment user is it may also be determined that go out the business implication of each characteristic index, the characteristic index reflection such as having is this striding equipment user value at PC end, as being made up of the pv of PC end (number of page views) amount, valid order amount etc.；What some characteristic index then reflected is this striding equipment user value on mobile terminals, as being made up of the number of starts of application program on mobile terminal (APP), pv amount, order volume etc..And according to reflection PC the end subscriber factor being worth and the factor reflecting that mobile phone users is worth distinguished, calculate the PC end of this striding equipment user and the total value of mobile terminal respectively.
In step S108, the characteristic index according to this striding equipment user, evaluate the value of this striding equipment user.
The value of striding equipment user can be determined according to the total value of each equipment calculated by the characteristic index (factor) of this striding equipment user's distinct device.
Such as, according to PC end and mobile terminal, characteristic index (factor namely gone out selected by the factor analysis) h to this striding equipment useri(i=1,2 ..., k) classification, it is assumed that the characteristic index (factor) that wherein reflection PC end subscriber is worth is { f1, f2..., fn, corresponding weight is { p1, p2..., pn}；The characteristic index (factor) that reflection mobile phone users is worth is { g1, g2..., gm, corresponding weight is { q1, q2..., qm}；Then this striding equipment user PC end subscriber total value isUser's total value of mobile terminal is
When the total value of this striding equipment user's distinct device is all bigger, it is determined that the value of this striding equipment user is high.Such as, when the total value of this striding equipment user's distinct device all can come before all striding equipment users 10%, it is believed that this striding equipment user has great value.Needing 10% merely illustrative explanation, and the unrestricted present invention are described, this numerical value can be arranged in actual applications according to demand.
Striding equipment user's Value Engineering Method 10 that present embodiment provides, logs in account number according to user, associates user's behavior on different devices, obtains the data on distinct device, and row index of going forward side by side screens；Again through factor analysis, the index filtered out is processed, thus obtaining the characteristic index of striding equipment user；The value of striding equipment user is assessed finally according to characteristic index.The method is possible not only to carry out value analysis for each striding equipment user, and when assessing striding equipment user and being worth, except the access behavior considering striding equipment user, also further contemplates the consuming behavior of striding equipment user.
It will be clearly understood that present disclosure describe how to be formed and use particular example, but principles of the invention is not limited to any details of these examples.On the contrary, based on the instruction of present disclosure, these principles can be applied to numerous other embodiments.
Fig. 2 is the flow chart of the another kind of striding equipment user's Value Engineering Method according to an illustrative embodiments.As in figure 2 it is shown, striding equipment user's Value Engineering Method 20 includes:
In step S202, obtain the data of the striding equipment user coming from least two equipment.
Such as, the user registered based on user logs in account number (such as user name, Email or phone number etc.) and striding equipment user behavior at least two equipment (such as PC equipment and the mobile terminal such as smart mobile phone, panel computer) is associated, and obtains the data on the described at least two equipment of this striding equipment user.Data can include data on described at least two equipment, that reflect each index of this striding equipment user browsing behavior and/or (placing an order) behavior of purchase.
In step S204, from the data of this striding equipment user, choose sampling sample.
In the data of acquired striding equipment user, not all data all must be used for being analyzed.The value of striding equipment user likely time to time change.It is thus possible, for instance the data of the striding equipment user that optional different sample time sections is to obtaining are sampled, and select sampling sample.
In certain embodiments, it is possible to according to different electric business, different business, select different sample time sections.Such as, for developing small-scale electricity business, owing to new user is more, it is shorter that the time period of sampling can select；And for the extensive electricity business of development stability, owing to old user is more, then sample time section can select longer.
Sampling sample in step S206, according to this striding equipment user chosen, it is determined that the index set of this striding equipment user.
Such as, at present in striding equipment is applied, user, typically by the APP in mobile terminal or browser two ways interactive browser or the purchase of passing through PC end, therefore when assessing striding equipment user and being worth, will consider the APP of PC end and mobile terminal simultaneously.Two equipment are also all considered by selected evaluation index as much as possible.For electricity business for, evaluation index such as listed in table 1:
Table 1
In order to reflect that striding equipment user is worth comprehensively, the index of selected sampling sample can reflect the value of striding equipment user as much as possible from different perspectives, but among these indexs, some is likely to use not quite, also has some to be likely to be repetition.It is thus desirable to these indexs are screened, so that it is determined that go out the valuable index set that independence is strong, have clear and definite business implication.
In certain embodiments, it is possible to adopt clustering methodology that sampling sample is screened.Clustering methodology be sort data into different classes or bunch a process, so the object in same bunch has a very big similarity, and the object between different bunches has very big diversity.When adopting clustering methodology screening sampling sample, it is possible to the practical situation according to data, select suitable clusters number.After having clustered, select index that is representative and that have clear and definite business implication to replace this class index from every apoplexy due to endogenous wind, so that it is determined that go out the index set of this striding equipment user.When the data volume of sample of sampling is little, it is possible to adopt hierarchical clustering method；When the data volume of sample of sampling is bigger, then can adopt k-means clustering procedure.Hierarchical clustering method and k-means clustering procedure are conventionally known to one of skill in the art, do not repeat them here.
In certain embodiments, it is also possible to adopt correlational analysis method that sampling sample is screened.Correlation analysis (correlationanalysis) method is whether to there is certain dependence between research phenomenon, and the phenomenon specifically having dependence is inquired into its related direction and degree of correlation, thus a kind of statistical method of the dependency relation studied between stochastic variable.When using correlational analysis method screening sampling sample, need to calculate the correlation coefficient between two between different indexs, and according to data practical situation, select suitable threshold value ρ, to the correlation coefficient two indices more than ρ, retain one of them, thus the index in sampling sample is screened, so that it is determined that go out the index set of this striding equipment user.
In step S208, the index set according to determined this striding equipment user, adopt factor analysis to determine the characteristic index of this striding equipment user.
Adopting factor analysis, the index set for determined this striding equipment user selects the suitable factor, namely the index in index set is sorted out, and wherein each factor is all referring to the linear combination of each index in mark set.When selective factor B, the selected factor need to reach an explanation degree preset, namely to overall explanation degree.This explanation degree can be arranged according to actual needs, for instance can being preset as 80%, the present invention is not limited.
Assume that the index after screening is for { X1... Xl), wherein each index XiAverage be μi.Selected because of quantum count be k, common factor is { h1... hk, corresponding explanation weight is Specific factor is { ε1... εl, then the factor model set up is:
Common factor { h therein1... hkIt is the characteristic index of this striding equipment user, each hi(i=1,2 ..., k) X can be expressed asi(i=1,2 ..., linear combination l).
Further, according to the characteristic index of this striding equipment user it may also be determined that go out the business implication of each characteristic index, for instance the characteristic index reflection having is this striding equipment user value at PC end, as being made up of the pv of PC end amount, valid order amount etc.；What some characteristic index then reflected is this striding equipment user value on mobile terminals, as being made up of the number of starts of application program on mobile terminal (APP), pv amount, order volume etc..
According to PC end and mobile terminal, to common factor hi(i=1,2 ..., k) classification, it is assumed that the factor that wherein reflection PC end subscriber is worth is { f1, f2..., fn, corresponding weight is { p1, p2..., pn}；The factor that reflection mobile phone users is worth is { g1, g2..., gm, corresponding weight is { q1, q2..., qm}；Then this striding equipment user PC end subscriber total value isUser's total value of mobile terminal is
In step S210, the user's total value according to the distinct device of this striding equipment user, evaluate the value of this striding equipment user.
Such as, the value of striding equipment user can be determined according to the user total value M of the user total value N of striding equipment user's PC end and mobile terminal.When the PC end of this striding equipment user and total value N and the M of mobile terminal are all bigger, it is determined that the value of this striding equipment user is high.Such as, when total value N and the M of the PC end of this striding equipment user and mobile terminal all can come before all striding equipment users 10%, it is believed that this striding equipment user has great value.Needing 10% merely illustrative explanation, and the unrestricted present invention are described, this numerical value can be arranged in actual applications according to demand.
Fig. 3 is the flow chart of another striding equipment user's Value Engineering Method according to an illustrative embodiments.Adopting striding equipment user's Value Engineering Method 10 or 20, after evaluating the value of each striding equipment user, as it is shown on figure 3, striding equipment user's Value Engineering Method 30 farther includes:
In step s 302, the value according to each striding equipment user, each striding equipment user is classified.
Such as, the large, medium and small grade according to the total value of each striding equipment user's distinct device, all striding equipment users are divided into 9 classes, each class striding equipment user has its respective business characteristic.
In certain embodiments, the division of the large, medium and small grade of the total value of striding equipment user's distinct device can be determined according to the ranking in all striding equipment users of the total value of the distinct device of striding equipment user, if the total value ranking of such as PC end is front 30%, then it is assumed that the total value of the PC end of this striding equipment user is big；Ranking is between front 70%～30%, then it is assumed that during the total value of the PC end of this striding equipment user is；Ranking is rear 30%, then it is assumed that the total value of the PC end of this striding equipment user is little.The grade classification of mobile terminal also described above, repeats no more.It should be noted that above-mentioned concrete numerical value is only signal, and the unrestricted present invention, this numerical value can be arranged in actual applications according to demand.
In step s 304, inhomogeneous striding equipment user is applied in different business.
Because each class striding equipment user has its respective business characteristic, therefore can inhomogeneous striding equipment user be applied in different business, adopt different operation ways to run, thus for the value optimizing management mode of different striding equipment users.
In certain embodiments, striding equipment user's Value Engineering Method 30 can further include step S306, the value assessment result according to the validity check striding equipment user of service application.
Such as, after sorted striding equipment user is applied in different business, if it find that its classifying quality is not good, discrimination is poor, then can reappraise according to preceding method the value of each striding equipment user, such as screening index, lifting factor explanation degree etc. from sampling sample again.If through above-mentioned improvement, classification application result still can not get a desired effect, then, after can again the data obtained being sampled, again the value of each striding equipment user is estimated according to striding equipment user's Value Engineering Method 10 or 20.
Striding equipment user's Value Engineering Method 30 that present embodiment provides, striding equipment user is classified by the value according to each striding equipment user evaluated further；Further according to the business characteristic of all kinds of striding equipment users, it is applied in different business, and adopts different operation ways.The method makes full use of the value of the striding equipment user evaluated, and different striding equipment users is taked different operation ways, optimizes service operation mode, and add Consumer's Experience.
It will be appreciated by those skilled in the art that all or part of step realizing above-mentioned embodiment is implemented as the computer program performed by CPU.When this computer program is performed by CPU, perform the above-mentioned functions that said method provided by the invention limits.Described program can be stored in a kind of computer-readable recording medium, and this storage medium can be read only memory, disk or CD etc..
Further, it should be noted that above-mentioned accompanying drawing is only schematically illustrating of the process included by the method for exemplary embodiment of the invention, rather than restriction purpose.It can be readily appreciated that above-mentioned process shown in the drawings is not intended that or limits the time sequencing of these process.It addition, be also easy to understand, these process can such as either synchronously or asynchronously perform in multiple modules.
Following for apparatus of the present invention embodiment, it is possible to be used for performing the inventive method embodiment.For the details not disclosed in apparatus of the present invention embodiment, refer to the inventive method embodiment.
Fig. 4 is the block diagram of a kind of striding equipment user's value analysis device according to an illustrative embodiments.As shown in Figure 4, striding equipment user value analysis device 40 includes: user data acquisition module 402, index set determine that module 404, characteristic index determine module 406, user's value assessment module 408.
Wherein user data acquisition module 402 is for obtaining the data of the striding equipment user coming from least two equipment.
Index set determines the data of the module 404 striding equipment user for obtaining according to user data acquisition module 402, it is determined that the index set of striding equipment user.
Characteristic index determines that module 406 for determining the index set of striding equipment user that module 404 determines according to index set, adopts factor analysis to determine the characteristic index of striding equipment user.
User's value assessment module 408 for determining the characteristic index of striding equipment user that module 406 determines, the value of assessment striding equipment user according to characteristic index.
The data of striding equipment user include: the data of striding equipment user reflection navigation patterns at least two equipment and/or the data of reflection purchasing behavior.
Striding equipment user's value analysis device 40 that present embodiment provides, it is possible not only to carry out value analysis for each striding equipment user, and when assessing striding equipment user and being worth, except the access behavior considering striding equipment user, also further contemplate the consuming behavior of striding equipment user.
Fig. 5 is the block diagram of the another kind of striding equipment user's value analysis device according to an illustrative embodiments.As it is shown in figure 5, striding equipment user's value analysis device 50 includes: user data acquisition module 502, index set determine that module 504, characteristic index determine module 506, user's value assessment module 508.
Wherein user data acquisition module 502 is for obtaining the data of the striding equipment user coming from least two equipment.
Index set determines the data of the module 504 striding equipment user for obtaining according to user data acquisition module 502, it is determined that the index set of striding equipment user.
Index set determines that module 504 includes: sampling submodule 5042 and index determine submodule 5044.
Sampling submodule 5042 is for choosing sampling sample the data of the striding equipment user obtained from user data acquisition module 502.
In certain embodiments, the sampling sample that sampling submodule 5042 is chosen is the selected sampling sample taken out from different sample time sections.
Index determines the sampling sample of the submodule 5044 striding equipment user for choosing according to sampling submodule 5042, it is determined that the index set of striding equipment user.
In certain embodiments, index determines that submodule 5044 is additionally operable to the sampling sample of the striding equipment user chosen according to sampling submodule 5042, adopts clustering methodology or correlational analysis method, it is determined that the index set of striding equipment user.
Characteristic index determines that module 506 for determining the index set of striding equipment user that module 504 determines according to index set, adopts factor analysis to determine the characteristic index of striding equipment user.
Characteristic index determines that module 506 includes: explanation degree determines submodule 5062 and selecting predictors submodule 5064.
Explanation degree determines that submodule 5062 is for explanation degree that certainty factor is analyzed.
Selecting predictors submodule 5064 is for determining, according to explanation degree, the explanation degree that submodule 5062 is determined, the index set for striding equipment user selects multiple factors, and wherein each factor is index set middle finger target linear combination.Wherein said multiple factor is the characteristic index of described striding equipment user.
User's value assessment module 508 for determining the characteristic index of striding equipment user that module 506 determines, the value of assessment striding equipment user according to characteristic index.
User's value assessment module 508 includes: first characteristic index classification submodule the 5082, first apparatus value determines submodule 5084 and value assessment submodule 5086.
The characteristic index of the striding equipment user that the first characteristic index classification submodule 5082 is determined for characteristic index is determined module 506 is divided into the respective characteristic index of at least two equipment.
First apparatus value determines the submodule 5084 respective characteristic index of at least two equipment for sorting out according to the first characteristic index classification submodule 5082, it is determined that at least two equipment respective user be worth.
Value assessment submodule 5086, for determining that the respective user of at least two equipment that submodule 5084 is determined is worth according to the first apparatus value, assesses the value of striding equipment user.
The data of striding equipment user include: the data of striding equipment user reflection navigation patterns at least two equipment and/or the data of reflection purchasing behavior.
Fig. 6 is the block diagram of another striding equipment user's value analysis device according to an illustrative embodiments.As shown in Figure 6, striding equipment user's value analysis device 60 and striding equipment user's value analysis device 40 or 50 are distinctive in that, except including user data acquisition module 402 or 502, index set determines module 404 or 504, characteristic index determines module 406 or 506, the outer (not shown) of user's value assessment module 408 or 508, also includes: striding equipment user's sort module 610 and business application module 612.
Wherein, striding equipment user's sort module 610 is used for when user's value assessment module 408 or 508 evaluates the value of all of striding equipment user, and each striding equipment user is classified by the value according to each striding equipment user.
In certain embodiments, striding equipment user sort module 610 includes: second characteristic index classification submodule the 6102, second apparatus value determines that submodule 6104 and striding equipment user classify submodule 6106.
Second characteristic index classification submodule 6102 is for being divided into the respective characteristic index of at least two equipment by the respective characteristic index of at least two equipment of each striding equipment user.
Second apparatus value determines that submodule 6104 is for the respective characteristic index of at least two equipment according to each striding equipment user, it is determined that the respective user of at least two equipment of each striding equipment user is worth.
Striding equipment user classifies submodule 6106 for the respective user's value of at least two equipment according to each striding equipment user, and each striding equipment user is classified.
Business application module 612 is for being applied to inhomogeneous striding equipment user in inhomogeneous business.
In certain embodiments, striding equipment user's value analysis device 60 also includes: user's inspection of value module 614, for after inhomogeneous striding equipment user is applied in inhomogeneous business by business application module 612, according to inhomogeneous striding equipment user application in corresponding service, the value assessment result of inspection striding equipment user.
Striding equipment user's value analysis device 60 that present embodiment provides, striding equipment user is classified by the value according to each striding equipment user evaluated further；Further according to the business characteristic of all kinds of striding equipment users, it is applied in different business, and adopts different operation ways.This device makes full use of the value of the striding equipment user evaluated, and different striding equipment users is taked different operation ways, optimizes service operation mode, and add Consumer's Experience.
It should be noted that the block diagram shown in above-mentioned accompanying drawing is functional entity, it is not necessary to must be corresponding with physically or logically independent entity.Software form can be adopted to realize these functional entitys, or in one or more hardware modules or integrated circuit, realize these functional entitys, or in heterogeneous networks and/or processor device and/or microcontroller device, realize these functional entitys.
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example embodiment described herein can be realized by software, it is also possible to the mode being combined necessary hardware by software is realized.Therefore, technical scheme according to embodiment of the present invention can embody with the form of software product, it (can be CD-ROM that this software product can be stored in a non-volatile memory medium, USB flash disk, portable hard drive etc.) in or network on, including some instructions so that computing equipment (can be personal computer, server, mobile terminal or the network equipment etc.) performs the method according to embodiment of the present invention.
More than it is particularly shown and described the illustrative embodiments of the present invention.It should be appreciated that the invention is not restricted to detailed construction described herein, set-up mode or realize method；On the contrary, it is intended to various amendments and equivalence in containing the spirit and scope being included in claims are arranged.
Claims (15)
1. striding equipment user's Value Engineering Method, it is characterised in that including:
Obtain the data of the striding equipment user coming from least two equipment；
Data according to described striding equipment user, it is determined that the index set of described striding equipment user；
Index set according to described striding equipment user, adopts factor analysis to determine the characteristic index of described striding equipment user；And
Characteristic index according to described striding equipment user, assesses the value of described striding equipment user.
2. method according to claim 1, it is characterised in that the characteristic index according to described striding equipment user, the value assessing described striding equipment user includes:
The characteristic index of described striding equipment user is divided into the described respective characteristic index of at least two equipment, and determines the weight that the described respective characteristic index of at least two equipment is corresponding；
Weight according to the described respective characteristic index of at least two equipment and correspondence thereof, it is determined that described at least two equipment respective user be worth；And
According to described at least two equipment, respective user is worth, and assesses the value of described striding equipment user.
3. method according to claim 1 and 2, it is characterised in that the data according to described striding equipment user, it is determined that the index set of described striding equipment user includes:
Sampling sample is chosen from the data of described striding equipment user；And
Sampling sample according to described striding equipment user, it is determined that the index set of described striding equipment user.
4. method according to claim 3, it is characterized in that, sampling sample according to described striding equipment user, determine that the index set of described striding equipment user includes: the sampling sample according to described striding equipment user, adopt clustering methodology or correlational analysis method, it is determined that the index set of described striding equipment user.
5. method according to claim 1 and 2, it is characterised in that the index set according to described striding equipment user, adopts factor analysis to determine that the characteristic index of described striding equipment user includes:
The explanation degree that certainty factor is analyzed；And
According to described explanation degree, the index set for described striding equipment user selects multiple factors, and wherein each factor is described index set middle finger target linear combination；
Wherein said multiple factor is the characteristic index of described striding equipment user.
6. method according to claim 1 and 2, it is characterised in that also include: when evaluating the value of all of described striding equipment user, the value according to each described striding equipment user, each described striding equipment user is classified；And inhomogeneous described striding equipment user is applied in inhomogeneous business.
7. method according to claim 6, it is characterized in that, after inhomogeneous described striding equipment user is applied in inhomogeneous business, also include: according to inhomogeneous described striding equipment user application in corresponding service, check the value assessment result of described striding equipment user.
8. method according to claim 1 and 2, it is characterised in that the data of described striding equipment user include: the data of described striding equipment user reflection navigation patterns on described at least two equipment and/or the data of reflection purchasing behavior.
9. striding equipment user's value analysis device, it is characterised in that including:
User data acquisition module, for obtaining the data of the striding equipment user coming from least two equipment；
Index set determines module, the data of the described striding equipment user for obtaining according to described user data acquisition module, it is determined that the index set of described striding equipment user；
Characteristic index determines module, for determining the index set of described striding equipment user that module determines according to described index set, adopts factor analysis to determine the characteristic index of described striding equipment user；And
User's value assessment module, for determining the characteristic index of described striding equipment user that module determines according to described characteristic index, assesses the value of described striding equipment user.
10. device according to claim 9, it is characterised in that described user's value assessment module includes:
Characteristic index classification submodule, the characteristic index for described characteristic index is determined described striding equipment user that module determines is divided into the described respective characteristic index of at least two equipment, and determines the weight that the described respective characteristic index of at least two equipment is corresponding；
Apparatus value determines submodule, for the weight of the described respective characteristic index of at least two equipment sorted out according to described first characteristic index classification submodule and correspondence thereof, it is determined that described at least two equipment respective user be worth；And
Value assessment submodule, for determining that the respective user of described at least two equipment that submodule is determined is worth according to described first apparatus value, assesses the value of described striding equipment user.
11. the device according to claim 9 or 10, it is characterised in that described index set determines that module includes:
Sampling submodule, for choosing sampling sample the data of the described striding equipment user obtained from described user data acquisition module；And
Index determines submodule, the sampling sample of the described striding equipment user for choosing according to described sampling submodule, it is determined that the index set of described striding equipment user.
12. the device according to claim 9 or 10, it is characterised in that described characteristic index determines that module includes:
Explanation degree determines submodule, for the explanation degree that certainty factor is analyzed；And
Selecting predictors submodule, for determining, according to described explanation degree, the described explanation degree that submodule is determined, the index set for described striding equipment user selects multiple factors, and wherein each factor is described index set middle finger target linear combination；
Wherein said multiple factor is the characteristic index of described striding equipment user.
13. the device according to claim 9 or 10, it is characterised in that also include:
Striding equipment user's sort module, is used for when described user's value assessment module estimation goes out the value of all of described striding equipment user, the value according to each described striding equipment user, each described striding equipment user is classified；And
Business application module, for being applied to inhomogeneous described striding equipment user in inhomogeneous business.
14. device according to claim 13, it is characterized in that, also include: user's inspection of value module, for after inhomogeneous described striding equipment user is applied in inhomogeneous business by described business application module, according to inhomogeneous described striding equipment user application in corresponding service, check the value assessment result of described striding equipment user.
15. the device according to claim 9 or 10, it is characterised in that the data of described striding equipment user include: the data of described striding equipment user reflection navigation patterns on described at least two equipment and/or the data of reflection purchasing behavior.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106294882A (en) * | 2016-08-30 | 2017-01-04 | 北京京东尚科信息技术有限公司 | Data digging method and device |
| CN107290967A (en) * | 2017-08-07 | 2017-10-24 | 合肥工业大学 | The automatic loading method and system of a kind of hydraulic press service function |
| CN107480187A (en) * | 2017-07-10 | 2017-12-15 | 北京京东尚科信息技术有限公司 | User's value category method and apparatus based on cluster analysis |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102053985A (en) * | 2009-11-11 | 2011-05-11 | 深圳市腾讯计算机系统有限公司 | Method and equipment for analyzing user value on line |
| CN103906027A (en) * | 2014-03-28 | 2014-07-02 | 中国联合网络通信集团有限公司 | User value evaluation method and system based on mobile user internet surfing behaviors |
| CN104050272A (en) * | 2014-06-25 | 2014-09-17 | 上海艾瑞市场咨询有限公司 | Cross-screen user behavior data statistics and analysis method and device |
| CN104834657A (en) * | 2014-08-27 | 2015-08-12 | 腾讯科技（北京）有限公司 | User behavior analysis method and servers |
-
2016
- 2016-02-19 CN CN201610094197.9A patent/CN105761110A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102053985A (en) * | 2009-11-11 | 2011-05-11 | 深圳市腾讯计算机系统有限公司 | Method and equipment for analyzing user value on line |
| CN103906027A (en) * | 2014-03-28 | 2014-07-02 | 中国联合网络通信集团有限公司 | User value evaluation method and system based on mobile user internet surfing behaviors |
| CN104050272A (en) * | 2014-06-25 | 2014-09-17 | 上海艾瑞市场咨询有限公司 | Cross-screen user behavior data statistics and analysis method and device |
| CN104834657A (en) * | 2014-08-27 | 2015-08-12 | 腾讯科技（北京）有限公司 | User behavior analysis method and servers |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106294882A (en) * | 2016-08-30 | 2017-01-04 | 北京京东尚科信息技术有限公司 | Data digging method and device |
| CN107480187A (en) * | 2017-07-10 | 2017-12-15 | 北京京东尚科信息技术有限公司 | User's value category method and apparatus based on cluster analysis |
| CN107290967A (en) * | 2017-08-07 | 2017-10-24 | 合肥工业大学 | The automatic loading method and system of a kind of hydraulic press service function |
| CN107290967B (en) * | 2017-08-07 | 2018-08-31 | 合肥工业大学 | A kind of automatic loading method and system of hydraulic press service function |
| US10571871B2 (en) | 2017-08-07 | 2020-02-25 | Hefei University Of Technology | Automatic loading system and method for service functions of hydraulic machine |
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