CN112235610B - Method, device and system for analyzing audience distribution of direct-request program - Google Patents
Method, device and system for analyzing audience distribution of direct-request program Download PDFInfo
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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]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/24—Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth, upstream requests
- H04N21/2407—Monitoring of transmitted content, e.g. distribution time, number of downloads
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
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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]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
- H04N21/25808—Management of client data
- H04N21/25841—Management of client data involving the geographical location of the client
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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]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
- H04N21/25866—Management of end-user data
Abstract
The invention relates to a method, a device and a system for analyzing audience rating distribution of direct-requested programs, which are used for performing data cleaning on acquired live broadcast original data and on-demand original data to obtain direct-requested structured data; associating the direct-on-demand structured data with a region IP library, and determining region information corresponding to the direct-on-demand structured data; extracting direct-on-demand homologous data in the direct-on-demand structured data; dividing the direct-request homologous data according to the region information corresponding to the direct-request homologous data to obtain at least one group of region direct-request homologous data; and respectively carrying out cross correlation matching on all region direct-demand homologous data with the program list information and the time information to determine audience distribution information. Therefore, live broadcast and on-demand data can be comprehensively counted, audience distribution is analyzed according to regions, programs and time, and errors of audience distribution statistics can be reduced, so that errors of television program delivery effect analysis of users are reduced, and accuracy of program delivery schemes is improved.
Description
Technical Field
The invention relates to the technical field of broadcast television, in particular to a method, a device and a system for analyzing direct-request program viewing distribution.
Background
The tv rating is the percentage of the number of people (or the number of households) watching a certain tv channel (or a certain tv program) to the total number of tv viewers (or the number of households) in a certain period. The television program audience rating statistics can help to know the playing effect of the television program, and the television program delivery can be adjusted in time according to the audience rating statistics, so that the audience rating of the television program is improved. Therefore, audience statistics for television programs are particularly important.
At present, the conventional audience rating statistics is based on live broadcast and on-demand independent statistics, when the audience rating of a program or a channel is directly analyzed, the live broadcast and on-demand independent statistics easily generate large errors, and the areas mainly targeted by some programs or advertisements are different, so that the audience rating situation difference of different areas is large, the audience rating of the directly analyzed program or channel easily causes large analysis errors on the playing effect of a television program, and the program delivery is influenced.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, and a system for analyzing audience rating distribution of a direct-requested program, so as to solve the problem in the prior art that live broadcast and on-demand broadcast are independently counted, audience rating differences in different regions are large, and audience ratings of directly analyzed programs or channels are likely to generate large errors, which results in large analysis errors on the broadcast effect of a television program, thereby affecting program delivery.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for analyzing the audience distribution of direct-request programs comprises the following steps:
acquiring live broadcast original data and on-demand original data;
performing data cleaning and gathering on the live broadcast original data and the on-demand original data to obtain direct on-demand structured data;
associating the direct-on-demand structured data with a pre-constructed region IP library, and determining region information corresponding to the direct-on-demand structured data;
extracting direct-on-demand homologous data in the direct-on-demand structured data;
dividing the direct-request homologous data according to the region information corresponding to the direct-request homologous data to obtain at least one group of region direct-request homologous data;
and respectively performing cross-correlation matching on all the region direct-on-demand homologous data with the pre-acquired program list information and the pre-divided time information, and determining audience distribution information analyzed according to regions, programs and time.
Further, in the above method for analyzing direct-request program viewing distribution, the direct-request structured data carries an MAC address;
the extracting of the direct-demand homologous data in the direct-demand structured data includes:
and extracting the direct-on-demand structured data with the same MAC address as the direct-on-demand homologous data.
Further, in the above method for analyzing the viewing distribution of the on-demand programs, the program information includes at least one program information; the time information comprises at least one time period;
the cross-correlation matching is performed on all the region direct-on-demand homologous data and the pre-acquired program list information and the pre-divided time information respectively, and audience distribution information analyzed according to regions, programs and time is determined, and the method comprises the following steps:
cross-correlation matching is carried out on all the region direct-on-demand homologous data with the program list information and the time information respectively, and program region direct-on-demand homologous data of each time slot of each program information corresponding to each region information is determined;
and determining the audience distribution information analyzed according to the region, the program and the time according to all the program region direct-ordering homologous data.
Further, the method for analyzing the audience distribution of the on-demand program further includes:
generating and outputting audience rating statistics output information according to the audience rating distribution information so that a user can check the audience rating statistics output information conveniently, and adjusting a program delivery scheme according to the audience rating statistics output information;
the audience statistics output information comprises chart information and/or text information.
Further, in the above method for analyzing viewing distribution of on-demand programs, the region IP library includes IP segment information and region information corresponding to the IP segment information;
the region information includes: a zone identity and a zone name;
the direct-on-demand structured data carries IP section information.
The invention also provides an analysis device for the audience rating distribution of the direct-demand program, which comprises the following components:
the acquisition module is used for acquiring live broadcast original data and on-demand original data;
the data cleaning module is used for cleaning and integrating the live broadcast original data and the on-demand original data to obtain direct on-demand structured data;
the region association module is used for associating the direct-on-demand structured data with a pre-constructed region IP (Internet protocol) library and determining region information corresponding to the direct-on-demand structured data;
the extraction module is used for extracting direct-on-demand homologous data in the direct-on-demand structured data;
the region division module is used for dividing the direct-request homologous data according to region information corresponding to the direct-request homologous data to obtain at least one group of region direct-request homologous data;
and the association matching module is used for respectively performing cross association matching on all the region direct-on-demand homologous data and the pre-acquired program list information and the pre-divided time information, and determining audience distribution information analyzed according to regions, programs and time.
Further, in the device for analyzing audience rating distribution of the on-demand program, the on-demand structured data carries an MAC address;
the extracting module is specifically configured to extract all the direct-request structured data with the same MAC address as the direct-request homologous data.
Further, in the above apparatus for analyzing direct program viewing distribution, the program information includes at least one program information; the time information comprises at least one time period;
the association matching module is specifically configured to perform cross-association matching on all the region direct-on-demand homologous data with the program guide information and the time information respectively, and determine program region direct-on-demand homologous data of each time slot of each program information corresponding to each region information;
and determining the audience distribution information analyzed according to the region, the program and the time according to all the program region direct-ordering homologous data.
Further, the apparatus for analyzing the viewing distribution of the on-demand program further includes: an output module;
the output module is used for generating and outputting audience rating statistics output information according to the audience rating distribution information so that a user can check the audience rating statistics output information conveniently, and adjusting a program release scheme according to the audience rating statistics output information; the audience statistics output information comprises chart information and/or text information.
The invention also provides an analysis system for the audience distribution of the direct-demand programs, which comprises the following steps: the system comprises a processor and a memory connected with the processor;
the memory is used for storing a computer program, and the computer program is at least used for executing the analysis method of the direct on-demand program viewing distribution;
the processor is used for calling and executing the computer program.
A method, a device and a system for analyzing audience distribution of direct-requested programs acquire direct-broadcast original data and on-demand original data; carrying out data cleaning and aggregation on the live broadcast original data and the on-demand original data to obtain direct on-demand structured data; associating the direct-on-demand structured data with a pre-constructed region IP library, and determining region information corresponding to the direct-on-demand structured data; extracting direct-on-demand homologous data in the direct-on-demand structured data; dividing the direct-on-demand homologous data according to region information corresponding to the direct-on-demand homologous data to obtain at least one group of region direct-on-demand homologous data; and respectively carrying out cross-correlation matching on all region direct-request homologous data with the pre-acquired program list information and the pre-divided time information, and determining audience distribution information analyzed according to regions, programs and time. By adopting the technical scheme of the invention, the data of live broadcast and on-demand can be comprehensively counted, the audience distribution is analyzed according to regions, programs and time, and the error of audience distribution counting can be reduced, so that the error of analysis of television program release effect of a user is reduced, the accuracy of a program release scheme is improved, and the program release value is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart provided by an embodiment of a method for analyzing a viewing distribution of a direct on demand program according to the present invention;
fig. 2 is a schematic structural diagram provided by an embodiment of the apparatus for analyzing audience distribution of direct-requested programs according to the present invention;
fig. 3 is a schematic diagram of a structure provided by an embodiment of the system for analyzing the viewing distribution of the on-demand programs according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
Fig. 1 is a flowchart provided in an embodiment of a method for analyzing direct on-demand program viewing distribution according to the present invention, and as shown in fig. 1, the method for analyzing direct on-demand program viewing distribution in the embodiment specifically includes the following steps:
s101, acquiring live broadcast original data and on-demand original data;
in the method for analyzing the audience distribution of the on-demand program, firstly, the acquired live broadcast original data and on-demand original data need to be acquired, where the present embodiment may acquire the live broadcast data and the on-demand data in an existing manner, and details are not described here.
S102, carrying out data cleaning and gathering on the live broadcast original data and the on-demand original data to obtain direct on-demand structured data;
after the live broadcast original data and the on-demand original data are obtained, data cleaning is carried out on the live broadcast original data and the on-demand original data, all data after data cleaning are collected, and direct on-demand structured data are obtained, so that comprehensive statistics of the live broadcast data and the on-demand data can be realized. In this embodiment, an ETL technology is used to perform data cleansing, so as to convert original data into structured data.
S103, correlating the direct on-demand structured data with a pre-constructed region IP library, and determining region information corresponding to the direct on-demand structured data;
after the direct-on-demand structured data after data cleaning is obtained, all the direct-on-demand structured data can be stored in a direct-on-demand database. And all the direct-on-demand structured data stored in the direct-on-demand database are associated with a pre-constructed region IP (Internet protocol) library, so that region information corresponding to the direct-on-demand structured data is determined. The regional IP library is preferably a medium and broad agreement IP library. The region IP library comprises IP section information and region information corresponding to the IP section information; the region information includes: a zone identity and a zone name. The IP section information is IP address information of a region.
All the direct-on-demand structured data carry IP section information, and after the direct-on-demand structured data are associated with a pre-constructed region IP library, the region information corresponding to the IP section information carried by the direct-on-demand structured data can be inquired from the region IP library.
S104, extracting direct-demand homologous data in the direct-demand structured data;
and after determining the region information corresponding to all the direct-on-demand structured data, extracting the direct-on-demand homologous data in all the direct-on-demand structured data. All the direct-on-demand structured data carry MAC addresses, and the direct-on-demand structured data with the same MAC addresses in the direct-on-demand database storing the direct-on-demand structured data are extracted and used as direct-on-demand homologous data. The homologous data has higher reliability for program audience distribution analysis than the non-homologous statistical data.
S105, dividing the direct-request homologous data according to the region information corresponding to the direct-request homologous data to obtain at least one group of region direct-request homologous data;
all the direct-on-demand structured data have corresponding region information, so that the direct-on-demand homologous data extracted from the direct-on-demand structured data also have corresponding region information, the direct-on-demand homologous data are divided according to the region information corresponding to the direct-on-demand homologous data, the direct-on-demand homologous data with the same region information are divided into one group to be used as the region direct-on-demand homologous data, and therefore at least one group of region direct-on-demand homologous data can be obtained. Wherein, a group of region direct-playing homologous data is all direct-playing homologous data of a region.
S106, respectively carrying out cross-correlation matching on all region direct-on-demand homologous data and the program list information acquired in advance and the time information divided in advance, and determining audience distribution information analyzed according to regions, programs and time.
And after at least one group of region direct-on-demand homologous data is obtained, performing cross correlation matching on all the region direct-on-demand homologous data and the pre-acquired program list information and the pre-divided time information respectively to determine viewing distribution information, wherein the viewing distribution information is obtained according to region, program and time analysis. The program information is program data derived by an EPG (electronic program guide) system, and the EPG system can provide program-related information for the inside. The program list information includes at least one program information. In addition, the time information includes at least one time period, in this embodiment, the time information may be divided in advance, and all the time in a day is divided into a plurality of time periods, for example, one hour is one time period, one day may be divided into 24 time periods, or ten minutes is one time period, and the like.
The steps are specifically as follows:
firstly, respectively carrying out cross correlation matching on all region direct-on-demand homologous data with program list information and time information, and determining program region direct-on-demand homologous data of each time slot of each program information corresponding to each region information;
in this embodiment, at least one group of region direct-on-demand homologous data may be obtained, and each group of region direct-on-demand homologous data is cross-associated and matched with the program guide information and the time information, so that region information corresponding to each group of region direct-on-demand homologous data and program region direct-on-demand homologous data of each time slot of each program information corresponding to each region information in the region information may be determined. Therefore, the direct-playing homologous data can be divided according to different regions, programs and time periods.
And secondly, determining audience distribution information analyzed according to regions, programs and time according to all program region direct-ordering homologous data.
After program region direct-on-demand homologous data of each time slot of each program information corresponding to each region information is obtained, viewing distribution information is determined according to all program region direct-on-demand homologous data, and the viewing distribution information is viewing data of all direct-on-demand homologous sources analyzed according to regions, programs and time slots. The viewing distribution information indicates viewing situations of different regions, different programs, and different time periods. The method has the advantages that the audience distribution condition analysis is carried out on different programs according to different regions and different time periods, and the statistical error of the audience condition of the programs affected by different regions can be reduced, so that the accuracy of the program release effect analysis is improved, users can conveniently release the programs, and the program release value is improved.
According to the method for analyzing audience distribution of the direct on-demand program, the obtained live broadcast original data and on-demand original data are subjected to data cleaning and are collected, and direct on-demand structured data are obtained; associating the direct-on-demand structured data with a pre-constructed region IP library, and determining region information corresponding to the direct-on-demand structured data; extracting direct-on-demand homologous data in the direct-on-demand structured data; dividing the direct-on-demand homologous data according to region information corresponding to the direct-on-demand homologous data to obtain at least one group of region direct-on-demand homologous data; and respectively performing cross-correlation matching on all region direct-on-demand homologous data with the pre-acquired program list information and the pre-divided time information, and determining audience distribution information analyzed according to regions, programs and time. Therefore, the data of live broadcast and on-demand broadcast can be comprehensively counted, the audience distribution is analyzed according to regions, programs and time, and the error of audience distribution statistics can be reduced, so that the error of television program delivery effect analysis of a user is reduced, the accuracy of a program delivery scheme is improved, and the program delivery value is improved.
Further, the method for analyzing the audience distribution of the direct on-demand program of the embodiment further includes:
and generating and outputting audience statistics output information according to the audience distribution information.
After the viewing distribution information is determined, viewing statistics output information is generated based on the viewing distribution information, and the viewing statistics output information may be chart information and/or text information, such as a line chart, a bar chart, a sector chart, and the like. For example, the areas may be divided in a map form, different viewing data ranges may be expressed by different colors, and viewing data of the areas in different time periods of each program may be visually expressed. And outputting the audience rating statistics output information so that a user can check the audience rating statistics output information, and adjusting a program delivery scheme according to the audience rating statistics output information so as to improve the program delivery value.
In order to be more comprehensive, the application also provides an analysis device for the viewing distribution of the direct-on-demand program, which corresponds to the analysis method for the viewing distribution of the direct-on-demand program provided by the embodiment of the invention.
Fig. 2 is a schematic structural diagram provided by an embodiment of an apparatus for analyzing direct on-demand program viewing distribution according to the present invention, and as shown in fig. 2, the apparatus for analyzing direct on-demand program viewing distribution according to the present embodiment includes: the system comprises an acquisition module 101, a data cleaning module 102, a region association module 103, an extraction module 104, a region division module 105 and an association matching module 106.
An obtaining module 101, configured to obtain live broadcast raw data and on-demand raw data;
the data cleaning module 102 is used for cleaning and integrating the live broadcast original data and the on-demand original data to obtain direct on-demand structured data;
the region association module 103 is configured to associate the direct-on-demand structured data with a pre-established region IP library, and determine region information corresponding to the direct-on-demand structured data;
the extraction module 104 is configured to extract direct video-on-demand homologous data from the direct video-on-demand structured data;
the region dividing module 105 is configured to divide the direct-play homologous data according to region information corresponding to the direct-play homologous data to obtain at least one group of region direct-play homologous data;
and the association matching module 106 is configured to perform cross-association matching on all region direct-on-demand homologous data with the pre-acquired program list information and the pre-divided time information, and determine viewing distribution information analyzed according to regions, programs, and time.
In the device for analyzing audience distribution of direct-on-demand programs in this embodiment, the data cleaning module 102 performs data cleaning and aggregation on the live broadcast original data and the on-demand original data acquired by the acquisition module 101 to obtain direct-on-demand structured data; the region association module 103 associates the direct-on-demand structured data with a pre-established region IP library, and determines region information corresponding to the direct-on-demand structured data; the extraction module 104 extracts the direct-on-demand homologous data in the direct-on-demand structured data; the region division module 105 divides the direct-on-demand homologous data according to region information corresponding to the direct-on-demand homologous data to obtain at least one group of region direct-on-demand homologous data; the association matching module 106 performs cross-association matching on all region direct-on-demand homologous data with the pre-acquired program list information and the pre-divided time information respectively, and determines viewing distribution information analyzed according to regions, programs and time. Therefore, the data of live broadcast and on-demand broadcast can be comprehensively counted, the audience distribution is analyzed according to regions, programs and time, and the error of audience distribution statistics can be reduced, so that the error of television program delivery effect analysis of a user is reduced, the accuracy of a program delivery scheme is improved, and the program delivery value is improved.
Further, in the apparatus for analyzing audience distribution of on-demand programs of this embodiment, the on-demand structured data carries the MAC address. The extracting module 104 is specifically configured to extract all direct-on-demand structured data with the same MAC address as direct-on-demand homologous data.
Further, in the apparatus for analyzing direct program viewing distribution of the present embodiment, the program information includes at least one program information; the time information includes at least one time period. The association matching module 106 is specifically configured to perform cross-association matching on all the region direct-on-demand homologous data with the program guide information and the time information, and determine program region direct-on-demand homologous data of each time slot of each program information corresponding to each region information; and determining audience distribution information analyzed according to the regions, the programs and the time according to the region direct-ordering homologous data of all the programs.
Furthermore, the apparatus for analyzing audience rating distribution of a direct-demand program of this embodiment further includes an output module, configured to generate and output audience rating statistics output information according to the audience rating distribution information, so that a user can view the audience rating statistics output information and adjust a program delivery scheme according to the audience rating statistics output information; the audience statistics output information includes graphical information and/or textual information.
With regard to the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be described in detail here.
Fig. 3 is a schematic structural diagram provided in an embodiment of the system for analyzing on-demand program viewing distribution according to the present invention, and as shown in fig. 3, the system for analyzing on-demand program viewing distribution according to the present embodiment includes a processor 21 and a memory 22 connected to the processor 21;
the memory 22 is used for storing a computer program, and the computer program is at least used for executing the method for analyzing the direct on-demand program audience distribution of the embodiment;
the processor 21 is used to call and execute the computer program.
The analysis system for audience distribution of the direct on-demand programs performs data cleaning and aggregation on the obtained live broadcast original data and on-demand original data to obtain direct on-demand structured data; associating the direct-on-demand structured data with a pre-constructed region IP library, and determining region information corresponding to the direct-on-demand structured data; extracting direct-on-demand homologous data in the direct-on-demand structured data; dividing the direct-on-demand homologous data according to region information corresponding to the direct-on-demand homologous data to obtain at least one group of region direct-on-demand homologous data; and respectively carrying out cross-correlation matching on all region direct-request homologous data with the pre-acquired program list information and the pre-divided time information, and determining audience distribution information analyzed according to regions, programs and time. Therefore, the data of live broadcast and on-demand broadcast can be comprehensively counted, the audience distribution is analyzed according to regions, programs and time, and the error of audience distribution statistics can be reduced, so that the error of television program delivery effect analysis of a user is reduced, the accuracy of a program delivery scheme is improved, and the program delivery value is improved.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that the terms "first," "second," and the like in the description of the present invention are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present invention, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that changes, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (8)
1. A method for analyzing audience distribution of direct-requested programs is characterized by comprising the following steps:
acquiring live broadcast original data and on-demand original data;
performing data cleaning and collecting on the live broadcast original data and the on-demand original data to obtain direct on-demand structured data;
associating the direct-on-demand structured data with a pre-constructed region IP library, and determining region information corresponding to the direct-on-demand structured data;
extracting direct-on-demand homologous data in the direct-on-demand structured data;
dividing the direct-request homologous data according to the region information corresponding to the direct-request homologous data to obtain at least one group of region direct-request homologous data;
respectively performing cross-correlation matching on all the region direct-on-demand homologous data with pre-acquired program list information and pre-divided time information, and determining audience distribution information analyzed according to regions, programs and time;
generating and outputting audience rating statistics output information according to the audience rating distribution information so that a user can check the audience rating statistics output information conveniently, and adjusting a program delivery scheme according to the audience rating statistics output information;
the audience statistics output information comprises chart information and/or text information.
2. The method for analyzing direct on demand program audience distribution according to claim 1, wherein the direct on demand structured data carries an MAC address;
the extracting of the direct-demand homologous data in the direct-demand structured data includes:
and extracting the direct-request structured data with the same MAC address as the direct-request homologous data.
3. The method for analyzing on-demand program viewing distribution according to claim 1, wherein the program list information includes at least one program information; the time information comprises at least one time period;
the cross-correlation matching is performed on all the region direct-on-demand homologous data and the pre-acquired program list information and the pre-divided time information respectively, and audience distribution information analyzed according to regions, programs and time is determined, and the method comprises the following steps:
cross-correlation matching is carried out on all the region direct-on-demand homologous data with the program list information and the time information respectively, and program region direct-on-demand homologous data of each time slot of each program information corresponding to each region information is determined;
and determining the audience distribution information analyzed according to the region, the program and the time according to all the program region direct-ordering homologous data.
4. The method for analyzing the viewing distribution of the on-demand program according to claim 1, wherein the regional IP library includes IP segment information and regional information corresponding to the IP segment information;
the region information includes: region identification and region name;
the direct-on-demand structured data carries IP section information.
5. An apparatus for analyzing a viewing distribution of a direct-requested program, comprising:
the acquisition module is used for acquiring live broadcast original data and on-demand original data;
the data cleaning module is used for cleaning and integrating the live broadcast original data and the on-demand original data to obtain direct on-demand structured data;
the region association module is used for associating the direct-on-demand structured data with a pre-constructed region IP (Internet protocol) library and determining region information corresponding to the direct-on-demand structured data;
the extraction module is used for extracting direct-program-playing homologous data in the direct-program-playing structured data;
the region division module is used for dividing the direct-request homologous data according to region information corresponding to the direct-request homologous data to obtain at least one group of region direct-request homologous data;
the correlation matching module is used for respectively performing cross correlation matching on all the region direct-on-demand homologous data and the pre-acquired program list information and the pre-divided time information, and determining audience distribution information analyzed according to regions, programs and time;
the output module is used for generating and outputting audience rating statistics output information according to the audience rating distribution information so that a user can check the audience rating statistics output information conveniently, and adjusting a program release scheme according to the audience rating statistics output information; the audience statistics output information comprises chart information and/or text information.
6. The apparatus for analyzing audience distribution of on-demand programs according to claim 5, wherein the on-demand structured data carries MAC addresses;
the extracting module is specifically configured to extract all direct-on-demand structured data with the same MAC address as the direct-on-demand homologous data.
7. The apparatus for analyzing on-demand program viewing distribution according to claim 5, wherein the program information includes at least one program information; the time information comprises at least one time period;
the association matching module is specifically configured to perform cross-association matching on all the region direct-request homologous data with the program guide information and the time information, and determine program region direct-request homologous data of each time slot of each program information corresponding to each region information;
and determining the audience distribution information analyzed according to the regions, the programs and the time according to all the program region direct-ordering homologous data.
8. An analysis system for audience distribution of on-demand programs, comprising: the system comprises a processor and a memory connected with the processor;
the memory is used for storing a computer program at least for executing the method for analyzing the direct on-demand program audience distribution according to any one of claims 1 to 4;
the processor is used for calling and executing the computer program.
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