CN112929753A - Set top box data acquisition system - Google Patents
Set top box data acquisition system Download PDFInfo
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- CN112929753A CN112929753A CN202110178802.1A CN202110178802A CN112929753A CN 112929753 A CN112929753 A CN 112929753A CN 202110178802 A CN202110178802 A CN 202110178802A CN 112929753 A CN112929753 A CN 112929753A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/4508—Management of client data or end-user data
- H04N21/4532—Management of client data or end-user data involving end-user characteristics, e.g. viewer profile, preferences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
- H04N21/4667—Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
- H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies
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Abstract
The invention discloses a set top box data acquisition system. The system comprises: the set-top box comprises a set-top box and a big data subsystem, wherein the set-top box comprises: the system comprises a foreground point burying module, a background static point burying module and a background dynamic point burying module; the background static embedded point module is used for acquiring static data input by a user, acquiring a first target log according to the static data and sending the first target log to the big data subsystem; the foreground embedded point module is connected with the background dynamic embedded point module and is used for acquiring dynamic data input by a user, determining registration information according to the dynamic data and sending the registration information to the background dynamic embedded point module; the background dynamic point burying module is connected with the big data subsystem and used for receiving the registration information, acquiring a second target log according to the registration information and sending the second target log to the big data subsystem.
Description
Technical Field
The embodiment of the invention relates to the technical field of set top boxes, in particular to a set top box data acquisition system.
Background
The IPTV, i.e. the interactive network television, is a brand-new technology that integrates various technologies such as internet, multimedia, communication, etc. into a whole by using a broadband cable television network, and provides various interactive services including digital television for home users. The user can enjoy the IPTV service at home. IPTV is different from both traditional analog cable tv and classical digital tv, because both traditional analog tv and classical digital tv have the features of frequency division, timing, unidirectional broadcast, etc. Although there are many technological innovations in classical digital television over analog television, there is only a change in the form of the signal, and there is no way to touch the way media content is disseminated.
The user terminal can be an IP set-top box + a television or a PC. IPTV can provide various digital media services including tv programs through internet protocols using the infrastructure of a cable tv network with a home tv set as a main terminal device.
The types and versions of set-top boxes are different all over the country at present, and the compatibility of JS is also different, so that tracking of user behavior logs is troublesome, a large amount of time is occupied during point burying work, and a large amount of manpower is consumed for development.
Disclosure of Invention
The embodiment of the invention provides a set top box data acquisition system, which acquires data in a mode of combining foreground and background embedded points, solves the problems of time consumption, poor compatibility and inflexible embedded points of the previous embedded points, and can be suitable for different machine types and full-service scenes.
In a first aspect, an embodiment of the present invention provides a set top box data acquisition system, including:
the set top box comprises a foreground embedded point module, a background static embedded point module and a background dynamic embedded point module;
the background static embedded point module is connected with the big data subsystem and used for acquiring static data input by a user, acquiring a first target log according to the static data and sending the first target log to the big data subsystem;
the foreground embedded point module is connected with the background dynamic embedded point module and is used for acquiring dynamic data input by a user, determining registration information according to the dynamic data and sending the registration information to the background dynamic embedded point module;
the background dynamic point burying module is connected with the big data subsystem and used for receiving the registration information, acquiring a second target log according to the registration information and sending the second target log to the big data subsystem;
the big data subsystem is connected with the background dynamic point burying module and the background static point burying module, and is used for receiving the first target log and the second target log.
Further, the method also comprises the following steps: a recommendation subsystem;
the big data subsystem is connected with the recommendation subsystem, and is further used for sending the first target log and the second target log to the recommendation subsystem;
the recommendation subsystem is connected with the big data subsystem and used for receiving the first target log and the second target log and determining recommendation information according to the first target log and the second target log.
Further, the method also comprises the following steps: a recommendation subsystem;
the set top box is connected with the recommendation subsystem, and is further used for sending the first target log and the second target log to the recommendation subsystem;
the recommendation subsystem is connected with the set-top box and used for receiving the first target log and the second target log and determining recommendation information according to the first target log and the second target log.
Further, the first target log comprises: at least one of a page click number log, an independent visitor number log, an order log, and a collection log.
Further, the second target log comprises: at least one of a page behavior log, a play behavior log, and a browse behavior log.
Further, sending the first target log to the big data subsystem includes:
and sending the first target log to the big data subsystem based on an FTP protocol.
Further, sending the second target log to the big data subsystem includes:
and sending the second target log to the big data subsystem based on an FTP protocol.
Further, the background static point burying module and the background dynamic point burying module are asynchronously processed.
Further, the big data subsystem is further configured to store the first target log and the second target log based on a file storage manner.
Further, obtaining a first target log according to the static data includes:
and acquiring a first target log through a service interface according to the static data.
The embodiment of the invention provides a set top box data acquisition system, which comprises: the set top box comprises a foreground embedded point module, a background static embedded point module and a background dynamic embedded point module; the background static embedded point module is connected with the big data subsystem and used for acquiring static data input by a user, acquiring a first target log according to the static data and sending the first target log to the big data subsystem; the foreground embedded point module is connected with the background dynamic embedded point module and is used for acquiring dynamic data input by a user, determining registration information according to the dynamic data and sending the registration information to the background dynamic embedded point module; the background dynamic point burying module is connected with the big data subsystem and used for receiving the registration information, acquiring a second target log according to the registration information and sending the second target log to the big data subsystem; the big data subsystem is connected with the background dynamic point burying module and the background static point burying module, and is used for receiving the first target log and the second target log and carrying out data acquisition in a mode of combining the foreground point burying and the background point burying, so that the problems of time consumption, poor compatibility and inflexible point burying of the previous point burying are solved, and the big data subsystem can be suitable for different machine types and all-service scenes.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of a set-top box data acquisition system according to a first embodiment of the present invention;
fig. 1a is a schematic structural diagram of another data acquisition system of a set-top box according to a first embodiment of the present invention;
fig. 2 is a flowchart of a set-top box data acquisition method in the second embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example one
Fig. 1 is a set top box data acquisition system according to an embodiment of the present invention, where the embodiment is applicable to a situation of performing set top box data acquisition, and the set top box data acquisition system includes: the set top box comprises a set top box 1 and a big data subsystem 2, wherein the set top box 1 comprises a foreground embedded point module 11, a background static embedded point module 12 and a background dynamic embedded point module 13;
the background static embedded point module is connected with the big data subsystem and used for acquiring static data input by a user, acquiring a first target log according to the static data and sending the first target log to the big data subsystem;
the foreground embedded point module is connected with the background dynamic embedded point module and is used for acquiring dynamic data input by a user, determining registration information according to the dynamic data and sending the registration information to the background dynamic embedded point module;
the background dynamic point burying module is connected with the big data subsystem and used for receiving the registration information, acquiring a second target log according to the registration information and sending the second target log to the big data subsystem;
the big data subsystem is connected with the background dynamic point burying module and the background static point burying module, and is used for receiving the first target log and the second target log.
Wherein the first target log comprises: at least one of a page click number log, a number of independent visitors log, a subscription log, and a collection log, the second target log comprising: at least one of a page behavior log, a play behavior log, and a browse behavior log.
The registration information may be page staying time length information and/or user watching time length information.
Optionally, the method further includes: a recommendation subsystem;
the big data subsystem is connected with the recommendation subsystem, and is further used for sending the first target log and the second target log to the recommendation subsystem;
the recommendation subsystem is connected with the big data subsystem and used for receiving the first target log and the second target log and determining recommendation information according to the first target log and the second target log.
Optionally, the method further includes: a recommendation subsystem;
the set top box is connected with the recommendation subsystem, and is further used for sending the first target log and the second target log to the recommendation subsystem;
the recommendation subsystem is connected with the set-top box and used for receiving the first target log and the second target log and determining recommendation information according to the first target log and the second target log.
Optionally, the first target log includes: at least one of a page click number log, an independent visitor number log, an order log, and a collection log.
Optionally, the second target log includes: at least one of a page behavior log, a play behavior log, and a browse behavior log.
Specifically, the browsing behavior may be determined according to a tracking access path. The page behavior log may include: page information and page dwell time, which may include: the current page dwell time may also include: the dwell time of a particular area in the page. The embodiments of the present invention are not limited in this regard.
Optionally, sending the first target log to the big data subsystem includes:
and sending the first target log to the big data subsystem based on an FTP protocol.
Optionally, sending the second target log to the big data subsystem includes:
and sending the second target log to the big data subsystem based on an FTP protocol.
Optionally, the background static point burying module and the background dynamic point burying module perform asynchronous processing.
Optionally, the big data subsystem is further configured to store the first target log and the second target log based on a file storage manner.
Optionally, obtaining the first target log according to the static data includes:
and acquiring a first target log through a service interface according to the static data.
The embodiment of the invention provides a log point burying frame, which is integrated by using a scheme that a background point is mainly buried and a front-end point is used for supplementing pit positions and is integrated into a big data subsystem and a recommendation subsystem.
As shown in fig. 1a, the set-top box data acquisition system includes: set-top box, big data subsystem and intelligent recommendation subsystem, the set-top box includes: the system comprises a foreground embedded point module, a background dynamic embedded point module and a background static embedded point module, wherein after a user enters the IPTV, the user stays on a page to operate, and the embedded point supplements pit information, stays for a long time, watches for a long time and accesses a path, and the foreground embedded point module is responsible for collecting the pit information; the background static embedded point module is directly put in a warehouse based on a service interface, stores the data of the static log, is also an independent service and is independently operated and distinguished from the service module; the background dynamic point burying module carries out certain processing treatment on the background according to the data uploaded by the foreground, and stores the treatment result into the log system; and the big data subsystem and the intelligent recommendation subsystem perform timing analysis according to the incoming log data to obtain operation data, and display the operation data to a foreground or a large screen.
In one specific example, the overall process is as follows: and the foreground public JS point burying module records time nodes and operation actions of the user entering the relevant service, and all data of the foreground is stored in cookie for tracking and recording. And the background service module calls the log module to perform asynchronous processing. And the background service module asynchronously processes foreground log data. And the log transmission is uniformly transmitted through an ftp protocol. And importing the data into a big data analysis module and an intelligent recommendation module for analysis processing.
In the embodiment of the invention, each module is independently developed, the problems of compatibility and later-stage upgrading are considered in the development process, an asynchronous processing scheme is adopted, the first node is developed and finished and then embedded into the service module, the log module is ensured not to be invasive to the service module, the whole development is finished, the function test, the integrated test and the online operation are started after the performance test are finished by testers.
The embodiment of the invention can efficiently acquire, upload and analyze the user data. The method has the advantages of no invasion to browsing behaviors of users and no invasion to service codes, and adopts the scheme integration that a background buried point is used as a main part and a front-end buried point supplements pit positions. And the log is integrated into a big data platform for data processing, and a complete set of complete solution is formed for the log from acquisition, processing and data display.
According to the technical scheme of the embodiment, a set top box data acquisition system is provided, and the set top box data acquisition system comprises: the set top box comprises a foreground embedded point module, a background static embedded point module and a background dynamic embedded point module; the background static embedded point module is connected with the big data subsystem and used for acquiring static data input by a user, acquiring a first target log according to the static data and sending the first target log to the big data subsystem; the foreground embedded point module is connected with the background dynamic embedded point module and is used for acquiring dynamic data input by a user, determining registration information according to the dynamic data and sending the registration information to the background dynamic embedded point module; the background dynamic point burying module is connected with the big data subsystem and used for receiving the registration information, acquiring a second target log according to the registration information and sending the second target log to the big data subsystem; the big data subsystem is connected with the background dynamic point burying module and the background static point burying module, and is used for receiving the first target log and the second target log and carrying out data acquisition in a mode of combining the foreground point burying and the background point burying, so that the problems of time consumption, poor compatibility and inflexible point burying of the previous point burying are solved, and the big data subsystem can be suitable for different machine types and all-service scenes.
Example two
Fig. 2 is a flowchart of a set-top box data acquisition method according to a second embodiment of the present invention. The embodiment is applicable to the situation of set-top box data acquisition, the apparatus can be implemented in a software and/or hardware manner, the apparatus can be integrated in any device providing a set-top box data acquisition function, as shown in fig. 2, the set-top box data acquisition method includes the following processes:
the method comprises the steps of obtaining target data input by a user, judging whether the target data input by the user are dynamic data or not, inputting the dynamic data into a foreground buried point module if the target data input by the user are dynamic data, determining registration information according to the dynamic data by the foreground buried point module, sending the registration information to a background dynamic buried point module, determining a second target log by the background dynamic buried point module according to the registration information, inputting static data into a background static buried point module if the target data input by the user are static data, and determining a first target log by the background static buried point module according to the static data.
Optionally, the big data subsystem sends the first target log and the second target log to the recommendation subsystem, and the recommendation subsystem receives the first target log and the second target log and determines recommendation information according to the first target log and the second target log.
Optionally, the method further includes: sending the first target log and the second target log to the recommendation subsystem; and the recommendation subsystem is used for receiving the first target log and the second target log and determining recommendation information according to the first target log and the second target log.
Wherein the first target log comprises: at least one of a page click number log, a number of independent visitors log, a subscription log, and a collection log, the second target log comprising: at least one of a page behavior log, a play behavior log, and a browse behavior log.
The registration information may be page staying time length information and/or user watching time length information.
Optionally, the first target log includes: at least one of a page click number log, an independent visitor number log, an order log, and a collection log.
Optionally, the second target log includes: at least one of a page behavior log, a play behavior log, and a browse behavior log.
Specifically, the browsing behavior may be determined according to a tracking access path. The page behavior log may include: page information and page dwell time, which may include: the current page dwell time may also include: the dwell time of a particular area in the page. The embodiments of the present invention are not limited in this regard.
Optionally, sending the first target log to the big data subsystem includes:
and sending the first target log to the big data subsystem based on an FTP protocol.
Optionally, sending the second target log to the big data subsystem includes:
and sending the second target log to the big data subsystem based on an FTP protocol.
Optionally, the background static point burying module and the background dynamic point burying module perform asynchronous processing.
Optionally, the big data subsystem is further configured to store the first target log and the second target log based on a file storage manner.
Optionally, obtaining the first target log according to the static data includes:
and acquiring a first target log through a service interface according to the static data.
The embodiment of the invention can efficiently acquire, upload and analyze the user data. The method has the advantages of no invasion to browsing behaviors of users and no invasion to service codes, and adopts the scheme integration that a background buried point is used as a main part and a front-end buried point supplements pit positions. And the log is integrated into a big data platform for data processing, and a complete set of complete solution is formed for the log from acquisition, processing and data display.
According to the technical scheme of the embodiment, a set top box data acquisition system is provided, and the set top box data acquisition system comprises: the set top box comprises a foreground embedded point module, a background static embedded point module and a background dynamic embedded point module; the background static embedded point module is connected with the big data subsystem and used for acquiring static data input by a user, acquiring a first target log according to the static data and sending the first target log to the big data subsystem; the foreground embedded point module is connected with the background dynamic embedded point module and is used for acquiring dynamic data input by a user, determining registration information according to the dynamic data and sending the registration information to the background dynamic embedded point module; the background dynamic point burying module is connected with the big data subsystem and used for receiving the registration information, acquiring a second target log according to the registration information and sending the second target log to the big data subsystem; the big data subsystem is connected with the background dynamic point burying module and the background static point burying module, and is used for receiving the first target log and the second target log and carrying out data acquisition in a mode of combining the foreground point burying and the background point burying, so that the problems of time consumption, poor compatibility and inflexible point burying of the previous point burying are solved, and the big data subsystem can be suitable for different machine types and all-service scenes.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A set-top box data acquisition system, comprising: the set-top box comprises a set-top box and a big data subsystem, wherein the set-top box comprises: the system comprises a foreground point burying module, a background static point burying module and a background dynamic point burying module;
the background static embedded point module is connected with the big data subsystem and used for acquiring static data input by a user, acquiring a first target log according to the static data and sending the first target log to the big data subsystem;
the foreground embedded point module is connected with the background dynamic embedded point module and is used for acquiring dynamic data input by a user, determining registration information according to the dynamic data and sending the registration information to the background dynamic embedded point module;
the background dynamic point burying module is connected with the big data subsystem and used for receiving the registration information, acquiring a second target log according to the registration information and sending the second target log to the big data subsystem;
the big data subsystem is connected with the background dynamic point burying module and the background static point burying module, and is used for receiving the first target log and the second target log.
2. The system of claim 1, further comprising: a recommendation subsystem;
the big data subsystem is connected with the recommendation subsystem, and is further used for sending the first target log and the second target log to the recommendation subsystem;
the recommendation subsystem is connected with the big data subsystem and used for receiving the first target log and the second target log and determining recommendation information according to the first target log and the second target log.
3. The system of claim 1, further comprising: a recommendation subsystem;
the set top box is connected with the recommendation subsystem, and is further used for sending the first target log and the second target log to the recommendation subsystem;
the recommendation subsystem is connected with the set-top box and used for receiving the first target log and the second target log and determining recommendation information according to the first target log and the second target log.
4. The system of claim 1, wherein the first target log comprises: at least one of a page click number log, an independent visitor number log, an order log, and a collection log.
5. The system of claim 1, wherein the second target log comprises: at least one of a page behavior log, a play behavior log, and a browse behavior log.
6. The system of claim 1, wherein sending the first target log to the big data subsystem comprises:
and sending the first target log to the big data subsystem based on an FTP protocol.
7. The system of claim 1, wherein sending the second target log to the big data subsystem comprises:
and sending the second target log to the big data subsystem based on an FTP protocol.
8. The system of claim 1, wherein the background static fixed point module and the background dynamic fixed point module process asynchronously.
9. The system of claim 1, wherein the big data subsystem is further configured to store the first target log and the second target log based on a file storage manner.
10. The system of claim 1, wherein obtaining a first target log from the static data comprises:
and acquiring a first target log through a service interface according to the static data.
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| CN110929204A (en) * | 2019-10-29 | 2020-03-27 | 苏宁云计算有限公司 | Method and device for determining attribution of pit bit data, computer equipment and storage medium |
| CN111124906A (en) * | 2019-12-17 | 2020-05-08 | 支付宝(杭州)信息技术有限公司 | Tracking method, compiling method and device based on dynamic embedded points and electronic equipment |
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| CN110489699A (en) * | 2019-08-16 | 2019-11-22 | 南京云帐房网络科技有限公司 | A kind of asynchronous data collection method and system |
| CN110929204A (en) * | 2019-10-29 | 2020-03-27 | 苏宁云计算有限公司 | Method and device for determining attribution of pit bit data, computer equipment and storage medium |
| CN111124906A (en) * | 2019-12-17 | 2020-05-08 | 支付宝(杭州)信息技术有限公司 | Tracking method, compiling method and device based on dynamic embedded points and electronic equipment |
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