CN109547821B - Television station channel viewing tendency evaluation method and device - Google Patents
Television station channel viewing tendency evaluation method and device 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
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- 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
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- 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
- H04N21/25891—Management of end-user data being end-user preferences
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- 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
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44204—Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched
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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
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44213—Monitoring of end-user related data
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- 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
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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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Abstract
The application provides a method and a device for evaluating channel viewing tendency of a television station, comprising the following steps: calculating preset time and watching duration of a preset channel according to the user attribute data and the user watching behavior data; calculating a channel evaluation index value according to the preset time, the viewing time of the preset channel and the preset audience weight; and evaluating the viewing tendency of the channel according to the channel evaluation index value. By adopting the scheme in the application, the viewing tendency condition of each channel of the television station can be scientifically, accurately, quickly and effectively evaluated.
Description
Technical Field
The present application relates to the field of broadcast television technologies, and in particular, to a method and an apparatus for evaluating a channel viewing tendency of a television station.
Background
At present, in the aspect of evaluating the viewing effect of a single channel of a television station, there is no scientific and effective evaluation method, and static statistics and comparison of data are mostly performed for a certain day or a certain time period of a certain day. The disadvantage of this method is obvious, the analysis time period of the evaluation result is narrow, and it is difficult to use the evaluation result for analyzing the whole audience situation from the perspective of the whole station or the whole channel.
In summary, the prior art has the following problems:
the channel viewing effect evaluation of the television station cannot reflect the overall viewing situation.
Disclosure of Invention
The embodiment of the application provides a method and a device for evaluating the channel viewing tendency of a television station, which are used for solving the technical problems in the prior art.
According to a first aspect of the embodiments of the present application, there is provided a method for estimating channel viewing tendency of a television station, including:
calculating preset time and watching duration of a preset channel according to the user attribute data and the user watching behavior data;
calculating a channel evaluation index value according to the preset time, the viewing time of the preset channel and the preset audience weight;
and evaluating the viewing tendency of the channel according to the channel evaluation index value.
According to a second aspect of the embodiments of the present application, there is provided an apparatus for estimating channel viewing tendency of a television station, comprising:
the first calculation module is used for calculating the preset time and the watching duration of the preset channel according to the user attribute data and the user watching behavior data;
the second calculation module is used for calculating a channel evaluation index value according to the preset time, the viewing time of the preset channel and the preset audience weight;
and the evaluation module is used for evaluating the viewing tendency of the channel according to the channel evaluation index value.
By adopting the method and the device for evaluating the television station channel viewing tendency provided by the embodiment of the application, the viewing condition is analyzed in multiple time dimensions and program type dimensions based on the overall data of a single channel in the television station, the viewing tendency change of the television station or the channel can be evaluated quickly and effectively, so that the bright spots and the deficiency of the television station in different time dimensions and the trend of the overall tendency can be known visually, and effective decision data support is provided for a manager of the television station or the channel.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart illustrating an implementation of a method for estimating channel viewing tendency of a television station according to an embodiment of the present application;
FIG. 2 is a schematic diagram showing a three-dimensional model structure of a data cube in an embodiment of the present application;
fig. 3 is a schematic structural diagram illustrating an apparatus for estimating channel viewing tendency of a television station according to an embodiment of the present application.
Detailed Description
The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Example 1
The embodiment of the application provides a method for evaluating the channel viewing tendency of a television station, which is explained below.
Fig. 1 is a schematic flow chart illustrating an implementation of a method for estimating channel viewing tendency of a television station according to an embodiment of the present application, where as shown in the figure, the method may include the following steps:
102, calculating a channel evaluation index value according to the preset time, the viewing time of a preset channel and the preset audience weight;
and 103, evaluating the viewing tendency of the channel according to the channel evaluation index value.
The television station channel viewing tendency evaluation method provided by the embodiment of the application can be used for analyzing the viewing situation of a single channel in a television station in multiple time dimensions and program type dimensions based on the overall data of the single channel, and can be used for quickly and effectively evaluating the viewing tendency change of the television station or the channel, so that the bright spots and the deficiency of the television station in different time dimensions and the trend of the overall tendency can be intuitively known, and effective decision data support is provided for a manager of the television station or the channel.
According to the method and the device, the preset time and the channel viewing duration of the preset channel are calculated by acquiring the attribute data and the viewing behavior data of each user, and then the channel evaluation index value can be calculated according to the preset time, the channel viewing duration of the preset channel and the preset audience weight.
In specific implementation, the attribute data and the viewing behavior data of the user can be acquired in a sampling mode, and the sampling time and frequency are not limited in the application.
In implementation, the user attribute data comprises a user weight and a location area; the user viewing behavior data comprises a channel to be viewed, a viewing starting time and a viewing ending time.
In an implementation, the user attribute data may include a user weight (or audience weight), a gender, an age, an education level, a location, and the like, and the viewing behavior data of the user may include a channel to be viewed, a viewing start time, a viewing end time, and the like.
In an implementation, before the calculating the preset time and the viewing duration of the preset channel according to the user attribute data and the viewing behavior data, the method further includes:
splitting the user viewing behavior data into user viewing behavior data of a plurality of unit time;
establishing a data cube from four dimensions of a channel, unit time, a user ID and user attributes according to user viewing behavior data and user attribute data of the unit time;
the data cube describes the user ID and user attributes viewed per channel per unit time.
In order to quickly calculate the index of the viewing data, the embodiment of the application can divide the viewing behavior data of the user from the viewing starting time to the viewing ending time into the viewing behavior data of the user in unit time (per minute), and in combination with the user attribute data, a data cube is established in four dimensions of a channel, unit time, a user ID and a user attribute, and the data cube describes which users are viewing in each channel and per minute and what the attributes of the users are.
The method for splitting the viewing behavior data of the user from the viewing start time to the viewing end time into the viewing behavior data in the user unit time may be as follows: traversing each piece of user viewing behavior data in the database to generate new and ordered user viewing behavior data, and then converting the user viewing behavior data into one or a plurality of new data with minutes as a time statistic unit aiming at one piece of user behavior data, wherein the viewing start time and the viewing end time of the new data are the current minutes.
The split mode is simple, convenient, fast and efficient to calculate.
In specific implementation, the viewing behavior data of the user is split from the viewing start time to the viewing end time, and another mode is as follows: all the existing user watching behavior data are traversed each time to determine whether the user watches in the target time period, and if so, the following situations can be also taken:
1, starting to watch at or before the beginning of a target time period, and finishing watching in the target time period;
starting to watch at the beginning or before the beginning of the target time period, and finishing watching at the end of the target time period or after the end of the target time period;
3, starting to watch in the target time period and finishing watching in the target time period;
and 4, starting to watch after the target time period starts, and finishing watching when or after the target time period finishes.
According to the embodiment of the application, a data cube is constructed, almost all viewing data indexes can be quickly and conveniently calculated from the data cube, and the complexity and the low efficiency of each user viewing behavior data in a counting time period are avoided when the viewing indexes in the specific time period are counted; the complexity and low efficiency of interception when the user watching time period crosses the statistical time period are avoided; the low efficiency that whether each user watching behavior data is in the range of the statistical channel or not is needed to be judged when the watching index of the specific channel is counted is avoided. The system complexity is greatly reduced, and the calculation efficiency is improved.
In specific implementation, the data cube may be established in the memory, and a specific establishment process may be as follows:
1, establishing a multiple dictionary, first, second, third and third, wherein the first dictionary is used for receiving the data of each channel, the second dictionary is used for receiving the data of each channel per minute, and the third dictionary is used for receiving the data of each channel per minute per user.
And 2, traversing a piece of user watching data, determining a certain minute for watching a certain channel, and creating a new key value pair in the minute, wherein the key is a user ID and the value is a user attribute structure body.
And 3, after traversing all the user viewing behavior data, finishing the establishment of the data cube.
According to the embodiment of the application, the establishment process of the data cube and the process of splitting the user viewing data into the per minute viewing data can be combined, and the minute data is directly filled into the data cube after the user viewing data is split into the minute-level data.
Fig. 2 is a schematic diagram showing a three-dimensional model structure of a data cube in the embodiment of the present application, as shown in the figure, a first dimension may be a channel, a second dimension may be time, a third dimension may be a city, each junction may be a local user list, and therefore, a hidden dimension is an attribute dimension of a single user, which may include age, education, a region where the user is located, gender, and the like.
In an implementation, the calculating a channel estimation index value according to the preset time, the viewing duration of the preset channel, and the preset audience weight includes:
calculating the following channel evaluation index values according to the preset time, the viewing duration of the preset channel and the preset audience weight:
in an implementation, the calculating a channel estimation index value according to the preset time, the viewing duration of the preset channel, and the preset audience weight further includes:
calculating the following channel evaluation index values according to the preset time, the viewing duration of the preset channel and the preset audience weight:
in the implementation, the calculating of the preset time and the viewing duration of the preset channel according to the user attribute data and the user viewing behavior data includes:
determining all user IDs in a preset channel and a preset time;
performing non-duplicate removal processing on the user ID, and obtaining a preset channel and all viewing users in preset time according to unit time;
and summing the user weights of all viewing users in the preset channel and the preset time obtained according to the unit time to obtain the viewing duration of the preset channel and the preset time.
Example 2
Based on the same inventive concept, the embodiment of the application provides a television station channel viewing tendency evaluation device, the principle of solving the technical problem is similar to the television station channel viewing tendency evaluation method, and repeated parts are not repeated.
Fig. 3 is a schematic structural diagram of an apparatus for estimating channel viewing tendency of a television station according to an embodiment of the present application, as shown in the figure, the apparatus includes:
the first calculating module 301 is configured to calculate a preset time and a viewing duration of a preset channel according to the user attribute data and the user viewing behavior data;
a second calculating module 302, configured to calculate a channel estimation index value according to the preset time, the viewing duration of a preset channel, and preset weights of each viewer;
and the evaluation module 303 is configured to evaluate the viewing tendency of the channel according to the channel evaluation index value.
The television station channel viewing tendency evaluation device provided by the embodiment of the application can be used for analyzing the viewing conditions of a television station in multiple time dimensions and program type dimensions based on the overall data of a single channel in the television station, and can be used for quickly and effectively evaluating the viewing tendency change of the television station or the channel, so that the bright spots and the deficiency of the television station in different time dimensions and the trend of the overall tendency can be intuitively known, and an effective decision data support is provided for a manager of the television station or the channel.
In an implementation, the apparatus may further include:
the data processing module is used for dividing the user watching behavior data into user watching behavior data of a plurality of unit time before calculating preset time and watching duration of a preset channel according to the user attribute data and the watching behavior data; establishing a data cube from four dimensions of a channel, unit time, a user ID and user attributes according to user viewing behavior data and user attribute data of the unit time;
the data cube describes the user ID and user attributes viewed per channel per unit time.
In an implementation, the second calculating module is configured to calculate the following channel estimation index values:
in an implementation, the second calculating module is configured to calculate the following channel estimation index values:
in an implementation, the first computing module may include:
the device comprises a determining unit, a judging unit and a judging unit, wherein the determining unit is used for determining all user IDs in a preset channel and preset time;
the processing unit is used for carrying out non-duplicate removal processing on the user ID and obtaining a preset channel and all viewing users in preset time according to unit time;
and the calculating unit is used for summing the user weights of the preset channel and all the viewing users in the preset time, which are obtained according to the unit time, so as to obtain the viewing duration of the preset channel and the preset time.
The television station channel viewing tendency evaluation device provided by the embodiment of the application can be used for analyzing the viewing conditions of a television station in multiple time dimensions and program type dimensions based on the overall data of a single channel in the television station, and can be used for quickly and effectively evaluating the viewing tendency change of the television station or the channel, so that the bright spots and the deficiency of the television station in different time dimensions and the trend of the overall tendency can be intuitively known, and an effective decision data support is provided for a manager of the television station or the channel.
Example 3
The embodiment of the present application will be described in detail by taking the evaluation of the channel viewing tendency of the central tv station as an example.
The embodiment of the present application exemplifies the share ratio of the audience, the time ratio of the audience, and the variation ratio of the audience as main contents.
1. Year-round audience share trend comparison
The audience share is the percentage value of the number of people watching a certain channel (program) to the number of all people watching television at the time, and the larger the value, the stronger the market competitiveness of the channel (program) in the time period is. By analyzing the trend of the data of the whole year, the audience rating trend changes of the audience rating effect of the whole program production whole of the channels, which programs in which time periods are in the high audience rating and which programs are in the low audience rating in a specific time period can be clearly seen. Through the analysis of the wave crests and the wave troughs of the data and the trend analysis of the trend height, operation basis and early warning can be provided for a management layer.
The calculation method comprises the following steps:
the annual audience share trends (such as 2017 and 2018) of the CCTV-1 comprehensive channels in the central vision can be compared according to the formula, and a curve chart is output to facilitate display, for example: the CCTV-1 channel audience share of 2 months and 1 day in 2017 is 5%, and the CCTV-1 channel audience share of 2 months and 1 day in 2018 is 15%.
2. Comparison of the whole day audience share trends
After the annual trend statistics, the integral trend of the audience share of a single day is analyzed in detail, and the program scheduling effect of the day can be effectively seen, so that high-efficiency programs can be directly tracked, and low-audience programs can be optimized.
The calculation method comprises the following steps:
the time-sharing trend comparison of the share of the CCTV-1 comprehensive channel in the central vision in all days can be obtained according to the formula: audience share trends per minute from periods 02:00 to 24:00 for three days 2017-10-31, 2018-10-30.
3. Program type viewing time comparison
On the basis of the all-day trend, the trend of programs of important categories is comprehensively compared, so that the viewing trend of important programs of a television station and the change caused by the program arrangement change are conveniently identified by channels, and the operation improvement is better fed back in time.
The calculation method comprises the following steps:
comparing the program watching time of each type of program in a channel single day, wherein the comparison shows the per-person watching time of each type of program, and the per-person watching time duration of each type of program in the channel single day
The viewing time comparison of various types of programs of CCTV-1 comprehensive channels in the central television can be obtained according to the formula, for example: in the days 2018-10-25 to 2018-10-31, various types of programs such as news/facts, art, drama, music, life service, etc. are rated for daily viewing time.
4. Program viewing variation trend analysis
Generally speaking, the television station defaults to the prime time of watching from 19 o 'clock to 22 o' clock every day, which basically determines the overall watching state, so that the broadcasting situation of the prime time is analyzed in more detail, and the comprehensive analysis is carried out on the watching change in the prime time within one month and the watching situation of the programs broadcasted in the prime time of the day, so as to provide an intuitive data trend analysis for a channel manager and make corresponding adjustment.
The calculation method comprises the following steps:
for example: according to the formula, the audience rating trend of the CCTV-1 comprehensive channel from 02:00 to 23:36 within the time period of 10 and 31 months in 2018 can be calculated, the audience rating change of the CCTV-1 comprehensive channel from 02 and 02 to 20 and 31 days in 10 and 31 months in 2018 within the prime time period (19:00-22:00) for 30 days can also be calculated, and the audience rating of each program broadcasted within the prime time period (19:00-22:00) within 10 and 31 days in 2018 can also be calculated.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (6)
1. A method for estimating the channel viewing tendency of a television station is characterized by comprising the following steps:
splitting the user viewing behavior data into user viewing behavior data of a plurality of unit times from viewing starting time to viewing ending time;
calculating preset time and watching duration of a preset channel according to the user attribute data and the user watching behavior data;
calculating a channel evaluation index value according to the preset time, the viewing time of the preset channel and the preset audience weight;
evaluating the viewing tendency of the channel according to the channel evaluation index value;
before the calculating of the preset time and the viewing duration of the preset channel according to the user attribute data and the viewing behavior data, the method further includes:
establishing a data cube from four dimensions of a channel, unit time, a user ID and user attributes according to user viewing behavior data and user attribute data of the unit time;
the data cube describes the user ID and user attributes watched by each channel in unit time;
the calculating of the channel evaluation index value according to the preset time, the viewing duration of the preset channel and the preset audience weight comprises the following steps: calculating the following channel evaluation index values according to the preset time, the viewing duration of the preset channel and the preset audience weight:
2. the method of claim 1, wherein calculating a channel estimation indicator value according to the preset time, the preset channel viewing duration and the preset viewer weights further comprises: calculating the following channel evaluation index values according to the preset time, the viewing duration of the preset channel and the preset audience weight:
3. the method of claim 1, wherein calculating the preset time and the viewing duration of the preset channel according to the user attribute data and the user viewing behavior data comprises:
determining all user IDs in a preset channel and a preset time;
performing non-duplicate removal processing on the user ID, and obtaining a preset channel and all viewing users in preset time according to unit time;
and summing the user weights of all viewing users in the preset channel and the preset time obtained according to the unit time to obtain the viewing duration of the preset channel and the preset time.
4. An apparatus for estimating a channel viewing tendency of a television station, comprising:
the first calculation module is used for splitting the user watching behavior data into the user watching behavior data of a plurality of unit times from the watching starting time to the watching ending time;
the first calculation module is further used for calculating preset time and watching duration of a preset channel according to the user attribute data and the user watching behavior data;
the second calculation module is used for calculating a channel evaluation index value according to the preset time, the viewing time of the preset channel and the preset audience weight;
the evaluation module is used for evaluating the viewing tendency of the channel according to the channel evaluation index value;
further comprising:
the data processing module is used for dividing the user watching behavior data into user watching behavior data of a plurality of unit time before calculating preset time and watching duration of a preset channel according to the user attribute data and the watching behavior data; establishing a data cube from four dimensions of a channel, unit time, a user ID and user attributes according to user viewing behavior data and user attribute data of the unit time;
the data cube describes the user ID and user attributes watched by each channel in unit time;
the second calculation module is used for calculating the following channel estimation index values:
5. the apparatus of claim 4, wherein the second calculating module is configured to calculate the following channel estimation index values:
6. the apparatus of claim 4, wherein the first computing module comprises:
the device comprises a determining unit, a judging unit and a judging unit, wherein the determining unit is used for determining all user IDs in a preset channel and preset time;
the processing unit is used for carrying out non-duplicate removal processing on the user ID and obtaining a preset channel and all viewing users in preset time according to unit time;
and the calculating unit is used for summing the user weights of the preset channel and all the viewing users in the preset time, which are obtained according to the unit time, so as to obtain the viewing duration of the preset channel and the preset time.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910039478.8A CN109547821B (en) | 2019-01-16 | 2019-01-16 | Television station channel viewing tendency evaluation method and device |
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| CN201910039478.8A CN109547821B (en) | 2019-01-16 | 2019-01-16 | Television station channel viewing tendency evaluation method and device |
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| CN109547821B true CN109547821B (en) | 2021-06-04 |
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