CN103607691A - Flow package recommendation method and device - Google Patents
Flow package recommendation method and device Download PDFInfo
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- CN103607691A CN103607691A CN201310611488.7A CN201310611488A CN103607691A CN 103607691 A CN103607691 A CN 103607691A CN 201310611488 A CN201310611488 A CN 201310611488A CN 103607691 A CN103607691 A CN 103607691A
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Abstract
The invention discloses a flow package recommendation method and device. The method includes the steps that the flow constitution of a mobile user is analyzed according to Internet-surfing information of the mobile user; the consumer preference of the mobile user is analyzed according to network behavior information of the mobile user; a corresponding flow package is recommended to the mobile user according to the obtained flow constitution and the consumer preference. By means of the method, the flow package which is more suitable for the user to user is recommended according to the practical conditions of the user, and therefore the user satisfaction and the user loyalty are promoted.
Description
Technical field
The present invention relates to telecommunication technology, espespecially a kind of flow set meal recommend method and device.
Background technology
At present, the mobile phone set meal of telecommunications industry is multifarious, various, if domestic consumer has darker professional knowledge to be difficult to distinguish any set meal, is not only and is applicable to oneself.Universal gradually along with 3G business, it is increasing that the consumption of wireless flow accounts for the ratio of mobile subscriber's telephone expenses expenditure, selects suitable set meal to become one of problem that mobile subscriber pays close attention to most.From operator's angle, flow operation can promote flow traffic growth, contains every user's average income (ARPU, Average Revenue Per User) value declines, reduce user's churn rate, meanwhile, can also comply with the variation tendency of mobile Internet development and user's request.
At present, research to flow correlation technique, focus on utilizing existing resource to improve the utilization ratio of network, such as, 3G traffic management and Optimization Platform system, end-to-end flux management and optimisation technique based on deep flow component analysis, application behavior identification, personal behavior identification basis, fundamentally solve the problems such as mobile Internet application extension, Bandwidth Management and user's experience.And by Data Detection Technology, data are carried out to multianalysis, and from far-end transmit leg, carry out flow control, reach optimum flow and control effect.
That is to say, existing flow correlation technique is only confined to how to improve 3G network utilization ratio, and user customized the reasonable consumption of flow, still, does not consider according to user's actual conditions and recommends to be more suitable for the flow set meal that user uses.That is to say, existing flow set meal recommend method is to carry out intelligently guiding to user's flow consumption, thereby can not be the customized optimal flow set meal of user.In addition, the dynamic service condition that existing flow marketing technology cannot further be followed the tracks of user, is the customized optimal set meal of user.
Summary of the invention
In order to solve the problems of the technologies described above, the invention provides a kind of flow set meal recommend method and device, can recommend to be more suitable for the flow set meal that user uses according to user's actual conditions, thereby promote user satisfaction and loyalty.
In order to reach the object of the invention, the invention provides a kind of flow set meal recommend method, comprising: the constitution of analyzing mobile subscriber according to mobile subscriber's internet information;
According to mobile subscriber's network behavioural information, analyze mobile subscriber's consumption preference;
In conjunction with the constitution obtaining and consumption preference, to mobile subscriber, recommend corresponding flow set meal.
Described analysis mobile subscriber's constitution comprises:
The online of obtaining mobile subscriber is single in detail, and analyzes mobile subscriber's the flow structure of consumer demand and calculate the shared ratio of each large class according to online is single in detail;
Each large class is segmented, and analyzed the flow structure of consumer demand of group and shared ratio thereof.
Described analysis mobile subscriber's consumption preference comprises:
According to the network behavior information obtaining, trace analysis mobile subscriber's internet behavior, classifies mobile subscriber according to service application content-preference.
Describedly to mobile subscriber, recommend corresponding flow set meal to comprise:
According to the constitution obtaining and consumption preference, determine that user makes earnest efforts the type of the business of use most;
According to mobile subscriber's consumer record and the user that judges, make earnest efforts the type of service of using most, for this mobile subscriber recommends corresponding flow set meal.
The present invention also provides a kind of flow set meal recommendation apparatus, at least comprises the first processing module, the second processing module, recommending module; Wherein,
The first processing module, for analyzing mobile subscriber's constitution according to mobile subscriber's internet information;
The second processing module, for analyzing mobile subscriber's consumption preference according to mobile subscriber's network behavioural information;
Recommending module, for the constitution in conjunction with obtaining and consumption preference, recommends corresponding flow set meal to mobile subscriber.
Described the first processing module specifically for: the online of obtaining mobile subscriber is single in detail, and analyzes mobile subscriber's the flow structure of consumer demand and calculate the shared ratio of each large class according to online is single in detail; Each large class is segmented, and analyzed the flow structure of consumer demand of group and shared ratio thereof.
Described the second processing module specifically for: according to the network behavior information obtaining, trace analysis mobile subscriber's internet behavior, classifies mobile subscriber according to service application content-preference.
Described recommending module specifically for: according to the constitution obtaining and consumption preference, determine that user makes earnest efforts the type of the business used most; According to mobile subscriber's consumer record and the user that judges, make earnest efforts the type of service of using most, for this mobile subscriber recommends corresponding flow set meal.
Compared with prior art, the present invention includes according to mobile subscriber's internet information analysis mobile subscriber's constitution; According to mobile subscriber's network behavioural information, analyze mobile subscriber's consumption preference; In conjunction with the constitution obtaining and consumption preference, to mobile subscriber, recommend corresponding flow set meal.By the inventive method, realized according to user's actual conditions and recommended to be more suitable for the flow set meal that user uses, thereby promoted user satisfaction and loyalty.
Other features and advantages of the present invention will be set forth in the following description, and, partly from specification, become apparent, or understand by implementing the present invention.Object of the present invention and other advantages can be realized and be obtained by specifically noted structure in specification, claims and accompanying drawing.
Accompanying drawing explanation
Accompanying drawing is used to provide the further understanding to technical solution of the present invention, and forms a part for specification, is used from explanation technical scheme of the present invention with the application's embodiment mono-, does not form the restriction to technical solution of the present invention.
Fig. 1 is the flow chart of set meal recommend method of the present invention;
Fig. 2 is the composition structural representation of set meal recommendation apparatus of the present invention.
Embodiment
For making the object, technical solutions and advantages of the present invention clearer, hereinafter in connection with accompanying drawing, embodiments of the invention are elaborated.It should be noted that, in the situation that not conflicting, the embodiment in the application and the feature in embodiment be combination in any mutually.
In the step shown in the flow chart of accompanying drawing, can in the computer system such as one group of computer executable instructions, carry out.And, although there is shown logical order in flow process, in some cases, can carry out shown or described step with the order being different from herein.
Fig. 1 is the flow chart of set meal recommend method of the present invention, as shown in Figure 1, comprising:
Step 100: the constitution of analyzing mobile subscriber according to mobile subscriber's internet information.
In this step, the online of obtaining mobile subscriber is single in detail, and analyzes mobile subscriber's the flow structure of consumer demand and calculate the shared ratio of each large class according to online is single in detail, such as, analysis obtains web page browsing and accounts for 40%, and timing bitcom accounts for 15%, mobile phone games account for 30%, and other accounts for 5%.Wherein, online is single can obtaining by Gn mouth in detail, belongs to those skilled in the art's common practise.Wherein, user's the online field that list comprises in detail mainly contains the information such as phone number, lane place coding, affiliated base coded, terminal type, type of service, time started, end time, online duration, object IP, URL address.Analyze mobile subscriber's the flow structure of consumer demand and calculate the shared ratio of each large class and mainly comprise: according to type of service, customer flow is segmented, by the business type field of surfing the Net in detail single as multimedia message, WAP online, WEB online, micro-letter, MSN, SKYPE, QQ, Fetion, PPTV, PPS, a sudden peal of thunder are looked at, mail, sudden peal of thunder download, electric donkey, other P2P business, mobile phone music, mobile phone games, DNS, mobile phone reading etc., can know clearly the use amount formation that user applies each large class.
In like manner, each large class is segmented, and analyzed the flow structure of consumer demand of group and shared ratio thereof.The web page browsing of take in large class is example, and analysis obtains movie channel Zhan45%， Sina of Sina football channel and accounts for 25%, and microblogging accounts for 15%, and other accounts for 15%.
According to field informations such as the lane place coding in the detailed list of online, affiliated base coded, time started, end times, analyze period of right time and the affiliated base station location of the flow of mobile subscriber's generation, such as: the 80% affiliated base station of online is Peking University base station; The generation time section of 60% flow is 10:00-13:30,23:00-0:30 etc.
By this step, obtained mobile subscriber's recessive information, such as, by above-mentioned analysis, can learn that this mobile subscriber likes to phone with mobile telephone game, like to see Internet video, and have deep love for football; And because most of flows all belong near base station university, and flow focuses mostly in time after school section, can infer that this mobile subscriber's identity is likely student, when recommending flow set meal, can recommend the set meal relevant to user identity like this.
Step 101: the consumption preference of analyzing mobile subscriber according to mobile subscriber's network behavioural information.
Can by Gn mouth, obtain mobile subscriber's original network behavior information, network behavior information comprises: subdistrict position, terminal type (IMEI), discharge pattern, access URL, access time started, end time, APN (APN), business are used information (User Agent), up-downgoing flow etc.
This step specifically comprises: according to the network behavior information obtaining, trace analysis mobile subscriber's internet behavior, classifies mobile subscriber according to service application content-preference; According to every user's average income (ARPU) value of user, in conjunction with user's consumption variation tendency of several months in past, user is divided into different class, such as high, medium and low third gear.It should be noted that, the strategy of the division of different class in operator, can there is different dividing mode as the case may be, such as, user's the average telephone expenses volume in past 3 months of take be to be divided foundation, can be divided into 200 yuan take telephone expenses last month between high-end user, 46-200 unit month telephone expenses be middle end subscriber, 46 yuan take telephone expenses next month as low end subscriber etc.
This step is by collecting mobile subscriber's flow track, excavated mobile subscriber's the core datas such as business hobby, behavioural characteristic, and then inferred user's point of interest place, for user recommends flow set meal, provides rational basis.Step 102: in conjunction with the constitution obtaining and consumption preference, recommend corresponding flow set meal to mobile subscriber.
In this step, first according to the constitution obtaining and consumption preference, mobile subscriber is tentatively judged, and definite user makes earnest efforts the type of the business of use most, such as: according to the type of service in the detailed list of online, constitution is sorted out to calculating, from video class, web page browsing class, mobile phone games class, instant chat class, mail class, download the several broad aspect of class and analyze, which class judges the business that user makes earnest efforts using most has.Then, the mobile subscriber's who provides according to the charge system of telecom operators consumer record is as the calling and called duration of every month, note traffic volume, 3G surfing flow etc., and in conjunction with the user that tentatively judges, make earnest efforts the type of service used most, for this mobile subscriber recommends corresponding flow set meal.According to flow is single in detail, judge the most frequently used business of user, then according to its consumption preference, judge whether to combine the set meal of made earnest efforts business, as Web TV.
By the inventive method, realized according to user's actual conditions and recommended to be more suitable for the flow set meal that user uses, thereby promoted user satisfaction and loyalty.
For instance, suppose 200 yuan take telephone expenses last month between high-end user, 46-200 unit month telephone expenses be middle end subscriber, 46 yuan take telephone expenses next month be low end subscriber.If certain user telephone expenses of 1 month are in the past 200 yuan of left and right, compare over 6 months, telephone expenses amount has obvious rising, and surfing flow focus mostly in movie channel be its consumption preference be video class, so, can tentatively judge this user for high-end, film hobby user; In addition, according to above-mentioned analysis, draw, this user exceeds the expense major part of existing set meal part for paying the flow outside set meal.Therefore, for this user, need to carry out set meal recommendation for the higher feature of accounting in the consumption of its set meal external flux, such as recommending to focus mostly in the special set meal bag of the video class business of movie channel for surfing flow, such as 15 yuan of monthly payments of UNICOM, Sohu are without limit flow set meal etc.
If this customer consumption value is always more stable, and the set meal having customized does not almost have surplus, probably this user often inquires about telephone expenses, and telephone expenses are relatively concerned about, can be according to its preference of surfing the Net for this user, the application of suitably having recommended, promotes the consumption of user to flow, and then recommends corresponding set meal, with this, user's request is transformed for data traffic flow amount, to have promoted flow scale, and flow have been transformed in order taking in, promoted whole flow and be worth.Or take video traffic as example, if user often sees video, but be subject to flow restriction, analyze list in detail and can excavate potential this client, and recommend video flow set meal bag to it, its object is the consumption preference according to user, on the basis that increases small charge, to user, recommends better business.
Fig. 2 is the composition structural representation of set meal recommendation apparatus of the present invention, as shown in Figure 2, at least comprises the first processing module, the second processing module, recommending module; Wherein,
The first processing module, for analyzing mobile subscriber's constitution according to mobile subscriber's internet information.Specifically for: the online of obtaining mobile subscriber is single in detail, and analyzes mobile subscriber's the flow structure of consumer demand and calculate the shared ratio of each large class according to online is single in detail; Each large class is segmented, and analyzed the flow structure of consumer demand of group and shared ratio thereof.
The second processing module, for analyzing mobile subscriber's consumption preference according to mobile subscriber's network behavioural information.Specifically for: according to the network behavior information obtaining, trace analysis mobile subscriber's internet behavior, classifies mobile subscriber according to service application content-preference.
Recommending module, for the constitution in conjunction with obtaining and consumption preference, recommends corresponding flow set meal to mobile subscriber.Specifically for: according to the constitution obtaining and consumption preference, determine that user makes earnest efforts the type of the business of use most; According to mobile subscriber's consumer record and the user that judges, make earnest efforts the type of service of using most, for this mobile subscriber recommends corresponding flow set meal.
Although the disclosed execution mode of the present invention as above, the execution mode that described content only adopts for ease of understanding the present invention, not in order to limit the present invention.Those of skill in the art under any the present invention; do not departing under the prerequisite of the disclosed spirit and scope of the present invention; can in the form of implementing and details, carry out any modification and variation; but scope of patent protection of the present invention, still must be as the criterion with the scope that appending claims was defined.
Claims (8)
1. a flow set meal recommend method, is characterized in that, comprising: the constitution of analyzing mobile subscriber according to mobile subscriber's internet information;
According to mobile subscriber's network behavioural information, analyze mobile subscriber's consumption preference;
In conjunction with the constitution obtaining and consumption preference, to mobile subscriber, recommend corresponding flow set meal.
2. flow set meal recommend method according to claim 1, is characterized in that, described analysis mobile subscriber's constitution comprises:
The online of obtaining mobile subscriber is single in detail, and analyzes mobile subscriber's the flow structure of consumer demand and calculate the shared ratio of each large class according to online is single in detail;
Each large class is segmented, and analyzed the flow structure of consumer demand of group and shared ratio thereof.
3. flow set meal recommend method according to claim 1, is characterized in that, described analysis mobile subscriber's consumption preference comprises:
According to the network behavior information obtaining, trace analysis mobile subscriber's internet behavior, classifies mobile subscriber according to service application content-preference.
4. according to the flow set meal recommend method described in claim 1～3 any one, it is characterized in that, describedly to mobile subscriber, recommend corresponding flow set meal to comprise:
According to the constitution obtaining and consumption preference, determine that user makes earnest efforts the type of the business of use most;
According to mobile subscriber's consumer record and the user that judges, make earnest efforts the type of service of using most, for this mobile subscriber recommends corresponding flow set meal.
5. a flow set meal recommendation apparatus, is characterized in that, at least comprises the first processing module, the second processing module, recommending module; Wherein,
The first processing module, for analyzing mobile subscriber's constitution according to mobile subscriber's internet information;
The second processing module, for analyzing mobile subscriber's consumption preference according to mobile subscriber's network behavioural information;
Recommending module, for the constitution in conjunction with obtaining and consumption preference, recommends corresponding flow set meal to mobile subscriber.
6. volume flow recommendation apparatus according to claim 5, it is characterized in that, described the first processing module specifically for: the online of obtaining mobile subscriber is single in detail, and analyzes mobile subscriber's the flow structure of consumer demand and calculate the shared ratio of each large class according to online is single in detail; Each large class is segmented, and analyzed the flow structure of consumer demand of group and shared ratio thereof.
7. flow set meal recommendation apparatus according to claim 5, it is characterized in that, described the second processing module specifically for: according to the network behavior information obtaining, trace analysis mobile subscriber's internet behavior, classifies mobile subscriber according to service application content-preference.
8. according to the flow set meal recommendation apparatus described in claim 6～7 any one, it is characterized in that, described recommending module specifically for: according to the constitution obtaining and consumption preference, determine that user makes earnest efforts the type of the business used most; According to mobile subscriber's consumer record and the user that judges, make earnest efforts the type of service of using most, for this mobile subscriber recommends corresponding flow set meal.
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