CN117750093A - Push method and device for television play content, electronic equipment and medium - Google Patents

Push method and device for television play content, electronic equipment and medium Download PDF

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Publication number
CN117750093A
CN117750093A CN202311690948.XA CN202311690948A CN117750093A CN 117750093 A CN117750093 A CN 117750093A CN 202311690948 A CN202311690948 A CN 202311690948A CN 117750093 A CN117750093 A CN 117750093A
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television
content
data
user
recommended
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朱从亮
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Tianyi Digital Life Technology Co Ltd
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Tianyi Digital Life Technology Co Ltd
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Abstract

The invention discloses a pushing method, a pushing device, electronic equipment and a medium of television play content, wherein the method comprises the following steps: acquiring recommended data of a television video port exposure recommended bit and carrying out data feature extraction processing to obtain playing content feature data; weighting the characteristic data of the broadcasting content to construct a television broadcasting content reporting contribution value and a television broadcasting content viewing contribution value; collecting behavior data of watching content of a user, and determining a dynamic operation recommendation coefficient of the user; and carrying out weighted calculation processing on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient, and updating recommendation data of the television video port exposure recommendation position according to the calculation result. The method and the device can improve the configuration efficiency, the hot spot updating speed and the content which is pushed in real time according to the interest change of the user, improve the experience of the user, and can be widely applied to the technical field of network television service recommendation.

Description

Push method and device for television play content, electronic equipment and medium
Technical Field
The present invention relates to the field of network television service recommendation technologies, and in particular, to a method and apparatus for pushing television broadcast content, an electronic device, and a medium.
Background
The interactive network television (IPTV) is a brand-new technology which utilizes a broadband network, integrates technologies such as Internet, multimedia, communication and the like, provides various interactive services including digital televisions for home users, provides more personalized, real-time and high-definition viewing experience, and can also recommend information of program contents according to viewing preferences of users in real time, and related technologies at present mainly adopt recommendation strategies based on manual configuration of product service personnel and simple provision of similar contents based on collection or historical data of user viewing clicks.
The existing television content recommendation method based on manual configuration of product service personnel is actually used for recommending according to layout content information of television programs, and is mainly used for recommending television program content by analyzing visual elements such as layout, colors, fonts and pictures of the television programs and text information such as program types, topics and emotions, but because the layout content is manually configured by the service personnel, the configuration efficiency is low, hot spots are not updated timely, recommended content surfaces are narrow, the content is old, users can see the program content basically uniformly, and the users watch fatigue; meanwhile, newly added or high-quality content cannot be timely and efficiently presented to a user, and the perception of the user is poor.
For existing recommendation strategies that provide similar content based on user viewing click collections or historical data, most are performed with similar content or the same type of recommendation strategy. Although these histories represent the direction of interest of the user to some extent, the recommended content and products are limited to this, and the information received by the user is too limited or the recommended content is repeatedly watched, so that the user cannot be led to new demands and new interests.
The related art therefore has at least the following problems: the data configuration efficiency is low, and the acquired user interest data is single in type, so that content information recommendation cannot be performed accurately and in real time, and the experience of a user is reduced.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems in the related art to some extent. Therefore, the invention provides a method, a device, electronic equipment and a medium for pushing television play content, which can improve configuration efficiency, hot spot updating speed and content pushed in real time according to interest changes of users, and improve experience of the users.
In one aspect, an embodiment of the present invention provides a method for pushing television broadcast content, including:
Acquiring recommended data of a television viewport recommended bit, and performing data feature extraction processing to obtain played content feature data, wherein the played content feature data comprises the television viewport recommended bit exposed data, television viewport recommended bit focusing data and user behavior data, and the user behavior data comprises the clicked times of television played content, television played content viewing time length data and television played content ordering times;
weighting the characteristic data of the broadcasting content to construct a television broadcasting content reporting contribution value and a television broadcasting content viewing contribution value;
collecting behavior data of watching content of a user, and determining a dynamic operation recommendation coefficient of the user;
and carrying out weighted calculation processing on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient, and updating recommendation data of the television video port exposure recommendation position according to the calculation result.
Optionally, acquiring recommended data of the television viewport exposure recommended bit and performing data feature extraction processing, where obtaining the play content feature data includes:
collecting recommendation data of a television viewport exposure recommendation bit;
cleaning and re-cleaning recommended data of the recommended television viewport exposure bit to obtain preprocessed recommended data of the recommended television viewport exposure bit;
And carrying out feature extraction processing based on the preprocessed recommended data of the television viewport exposure recommended bit to obtain the playing content feature data.
Optionally, weight giving processing is performed on the playing content feature data to construct a television playing content reporting contribution value and a television playing content viewing contribution value, including:
determining the duty ratio data of the play content characteristic data in the preset period frequency according to the play content characteristic data;
determining weights corresponding to the playing content characteristic data, wherein the weights of the playing content characteristic data comprise television viewport recommendation bit exposure data weights, television viewport recommendation bit focus-falling data weights and user behavior data weights;
and combining the weight of the broadcasting content characteristic data and the duty ratio data of the broadcasting content characteristic data to construct a television broadcasting content reporting contribution value and a television broadcasting content viewing contribution value.
Optionally, the calculation expression of the contribution value of the television broadcast content is:
E a ＝(Age 1 *P 1 +Age 2 *P 2 +Age 3 *P 3 )*t
in the above, E a The value of contribution degree, age, of reporting television playing content 1 The recommended bit exposure data duty ratio of the television viewing port is represented, age 2 Age represents the focal data duty ratio of the recommended position of the television viewing port 3 Representing the clicked times of the television playing content, P 1 Indicating the weight of the recommended bit exposure data of the television viewport, P 2 Representing the weight of the television viewport recommended bit focus-down data, P 3 The weight of the clicked times of the television playing content is represented, and t represents the preset cycle frequency.
Optionally, the calculation expression of the television broadcast content audience rating contribution value is:
E b ＝(Age 4 +Age 5 )*P 4 *t
in the above, E b Age representing audience contribution value of television broadcast content 4 Data duty ratio, age, representing viewing time of television broadcast content 5 Representing the ordering frequency of television playing content and P 4 The data weight of the television broadcast content viewing time length and the ordering frequency weight of the television broadcast content are represented, and t represents the preset cycle frequency.
Optionally, collecting behavior data of viewing content of a user, and determining a dynamic operation recommendation coefficient of the user includes:
collecting user watching content behavior data, wherein the user watching content behavior data comprises television content classification data, staff member data and business type data;
performing data cleaning and re-processing on the user watching content behavior data to obtain preprocessed user watching content behavior data;
determining the duty ratio of the user watching content behavior data in a preset period frequency according to the preprocessed user watching content behavior data;
determining corresponding user watching content behavior data coefficients according to the user watching content behavior data duty ratio;
And determining a dynamic operation recommendation coefficient of the user according to the content watching behavior data coefficient of the user and the content watching behavior data duty ratio of the user.
Optionally, performing weighted calculation processing on the contribution value of the report of the television broadcast content, the audience contribution value of the television broadcast content and the dynamic operation recommendation coefficient of the user, and updating recommendation data of the television viewport exposure recommendation bit according to a calculation result, including:
weighting calculation is carried out on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient to obtain a calculation result;
constructing a preset exposure coefficient threshold;
and selecting television broadcasting contents corresponding to which the calculation result is larger than the preset exposure coefficient threshold value, and updating recommended data of the television viewport exposure recommended bit.
In another aspect, an embodiment of the present invention provides a device for pushing content played by a television, including:
the first module is used for acquiring recommended data of the television viewing port recommended bit and carrying out data feature extraction processing to obtain broadcasting content feature data, wherein the broadcasting content feature data comprises the television viewing port recommended bit exposure data, television viewing port recommended bit focusing data and user behavior data, and the user behavior data comprises the clicked times of the broadcasting content, the television broadcasting content viewing time length data and the broadcasting content ordering times;
The second module is used for giving weight to the characteristic data of the playing content and constructing a television playing content reporting contribution value and a television playing content viewing contribution value;
the third module is used for collecting behavior data of the content watched by the user and determining a dynamic operation recommendation coefficient of the user;
and the fourth module is used for carrying out weighted calculation processing on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient, and updating recommendation data of the television viewport exposure recommendation position according to the calculation result.
Optionally, the first module is specifically configured to:
collecting recommendation data of a television viewport exposure recommendation bit;
cleaning and re-cleaning recommended data of the recommended television viewport exposure bit to obtain preprocessed recommended data of the recommended television viewport exposure bit;
and carrying out feature extraction processing based on the preprocessed recommended data of the television viewport exposure recommended bit to obtain the playing content feature data.
Optionally, the second module is specifically configured to:
determining the duty ratio data of the play content characteristic data in the preset period frequency according to the play content characteristic data;
determining weights corresponding to the playing content characteristic data, wherein the weights of the playing content characteristic data comprise television viewport recommendation bit exposure data weights, television viewport recommendation bit focus-falling data weights and user behavior data weights;
Combining the weight of the broadcasting content characteristic data and the duty ratio data of the broadcasting content characteristic data to construct a television broadcasting content reporting contribution value and a television broadcasting content viewing contribution value;
the calculation expression of the contribution value of the television broadcasting content report is as follows:
E a ＝(Age 1 *P 1 +Age 2 *P 2 +Age 3 *P 3 )*t
in the above, E a The value of contribution degree, age, of reporting television playing content 1 The recommended bit exposure data duty ratio of the television viewing port is represented, age 2 Representing television viewport recommended bit decoking data duty cycle，Age 3 Representing the clicked times of the television playing content, P 1 Indicating the weight of the recommended bit exposure data of the television viewport, P 2 Representing the weight of the television viewport recommended bit focus-down data, P 3 The method comprises the steps of representing the clicked times weight of television playing content, and t represents preset periodic frequency;
the calculation expression of the television broadcast content audience rating contribution value is as follows:
E b ＝(Age 4 +Age 5 )*P 4 *t
in the above, E b Age representing audience contribution value of television broadcast content 4 Data duty ratio, age, representing viewing time of television broadcast content 5 Representing the ordering frequency of television playing content and P 4 The data weight of the television broadcast content viewing time length and the ordering frequency weight of the television broadcast content are represented, and t represents the preset cycle frequency.
Optionally, the third module is specifically configured to:
collecting user watching content behavior data, wherein the user watching content behavior data comprises television content classification data, staff member data and business type data;
Performing data cleaning and re-processing on the user watching content behavior data to obtain preprocessed user watching content behavior data;
determining the duty ratio of the user watching content behavior data in a preset period frequency according to the preprocessed user watching content behavior data;
determining corresponding user watching content behavior data coefficients according to the user watching content behavior data duty ratio;
and determining a dynamic operation recommendation coefficient of the user according to the content watching behavior data coefficient of the user and the content watching behavior data duty ratio of the user.
Optionally, the fourth module is specifically configured to:
weighting calculation is carried out on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient to obtain a calculation result;
constructing a preset exposure coefficient threshold;
and selecting television broadcasting contents corresponding to which the calculation result is larger than the preset exposure coefficient threshold value, and updating recommended data of the television viewport exposure recommended bit.
In another aspect, an embodiment of the present invention provides an electronic device, including: a processor and a memory; the memory is used for storing programs; the processor executes the program to realize the push method of the television play content.
In another aspect, an embodiment of the present invention provides a computer storage medium, in which a program executable by a processor is stored, where the program executable by the processor is used to implement the method for pushing television broadcast content.
The method, the device, the electronic equipment and the medium have the beneficial effects that: firstly, recommendation data of a television viewport exposure recommendation position is obtained and data characteristic extraction processing is carried out to obtain play content characteristic data, wherein the play content characteristic data comprises television viewport recommendation position exposure data, television viewport recommendation position focus-falling data and user behavior data.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate and do not limit the invention.
FIG. 1 is a schematic diagram of an implementation environment for pushing content of a television broadcast according to an embodiment of the present invention;
fig. 2 is a flow chart of a method for pushing television broadcast content according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of a combination weight judgment of a television play content push strategy according to an embodiment of the present invention;
fig. 4 is a schematic flow chart of data feature extraction processing according to an embodiment of the present invention;
FIG. 5 is a schematic flow chart of a weight assignment process according to an embodiment of the present invention;
FIG. 6 is a schematic flow chart of determining a recommendation coefficient of dynamic operation of a user according to an embodiment of the present invention;
fig. 7 is a schematic flow chart of a weighting calculation process according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a pushing device for playing content of a television according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
Fig. 10 is a block diagram of a computer system suitable for implementing an electronic device according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It should be noted that although functional block diagrams are depicted as block diagrams, and logical sequences are shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the block diagrams in the system. The terms first/S100, second/S200, and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
It can be understood that the method for pushing the television playing content provided by the embodiment of the invention can be applied to any computer equipment with data processing and calculating capabilities, and the computer equipment can be various terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or is a server cluster or a distributed system formed by a plurality of physical servers, or is a cloud server for providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network ), basic cloud computing services such as big data and artificial intelligence platforms, and the like. Alternatively, the terminal is a smart phone, a tablet computer, a notebook computer, a desktop computer, or the like, but is not limited thereto.
FIG. 1 is a schematic view of an embodiment of the invention. Referring to fig. 1, the implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected through a network in a wireless or wired mode to complete data transmission and exchange.
The server 101 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs (Content Delivery Network, content delivery networks), basic cloud computing services such as big data and artificial intelligent platforms, and the like.
In addition, server 101 may also be a node server in a blockchain network. The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like.
The terminal 102 may be, but is not limited to, a smart phone, tablet, notebook, desktop, smart box, smart watch, etc. The terminal 102 and the server 101 may be directly or indirectly connected through wired or wireless communication, which is not limited in this embodiment of the present invention.
Based on the implementation environment shown in fig. 1, the embodiment of the present invention provides a method for pushing tv broadcast content, and the following description will take an example that the method for pushing tv broadcast content is applied to the server 101 as an application, and it will be understood that the method for pushing tv broadcast content may also be applied to the terminal 102.
Referring to fig. 2, fig. 2 is a flowchart of a method for pushing tv broadcast content applied to a server according to an embodiment of the present invention, where an execution body of the method for pushing tv broadcast content may be any one of the foregoing computer devices. Referring to fig. 2, the method includes the steps of:
s100, acquiring recommended data of a television viewing port recommended bit and performing data feature extraction processing to obtain playing content feature data, wherein the playing content feature data comprises the television viewing port recommended bit exposed data, television viewing port recommended bit focus-falling data and user behavior data, and the user behavior data comprises the number of times that television playing content is clicked, television playing content viewing time length data and television playing content ordering times;
it should be noted that, in some embodiments, as shown in fig. 4, step S100 may include: s101, acquiring recommendation data of a television viewport exposure recommendation bit; s102, cleaning and re-processing recommended data of the recommended television viewport exposure bit to obtain the preprocessed recommended data of the recommended television viewport exposure bit; and S103, performing feature extraction processing based on the preprocessed recommended data of the television viewport exposure recommended bit to obtain the playing content feature data.
In some specific embodiments, the acquisition device may collect recommended data of the television viewport exposure recommended bit, where the acquisition device may be composed of a PCMCIA interface interconnected with the set top box and the CAM and a data transmission module, where the PCMCIA interface in the embodiment of the present invention is connected to a PCMCIA mother slot of the digital television device, and the PCMCIA interface of the CAM card is connected to the PCMCIA interface in the embodiment of the present invention, so as to implement interconnection and intercommunication of the three, and the collected data is reported to the control end by the data transmission module (such as USB and network card) to obtain recommended data of the television viewport exposure recommended bit.
In some embodiments, first, the recommendation data for the television viewport exposure recommendation bits is read, which may be done using an appropriate programming language and library, such as a CSV file or SQL database using the pandas library of Python. Further performing data cleaning processing, and before performing data deduplication processing, performing data cleaning is required. The data deduplication process may be started after the data is cleaned, repeated recommended entries may exist for the recommended data of the television viewport exposure recommendation bit, for example, the same program or advertisement is recommended multiple times within the same time period, the repeated entries may be deleted using a deduplication function in the programming language or a deduplication operation in the database, the deduplication process is finally completed, the cleaned and deduplicated data is stored in a file or database, and the results may be optionally visualized to better understand the data and discovery patterns.
In some embodiments, a feature extraction method is selected, where the feature extraction method includes a statistical method, a machine learning method, a deep learning method, and the like, and different features are extracted from the recommended data according to the selected feature extraction method, for example, a program audience rating, an audience age and gender distribution, a viewing time, and the like may be extracted as features, and in addition, extraction timing features, for example, a recommended time sequence mode, a viewing behavior of an audience, and the like, may be considered.
In the specific embodiment of the present invention, the exposure data of the recommended position of the television viewport indicates the exposure time of the television viewport to the content in the evaluation period, the focus-falling data of the recommended position of the television viewport indicates the focus-falling time of the cursor triggered by the television viewport to the content in the evaluation period, the clicked time of the television playing content, that is, the number of times of clicking the recommended position by the user, indicates the number of times of clicking the content triggered in the evaluation period, the viewing time data of the television playing content indicates the total time of the viewing behavior of the content in the user in the evaluation period, and the ordering time of the television playing content indicates the ordering time of the content triggered by the content in the evaluation period.
Further, it should be noted that, the tv viewport recommended positions are indicated on the tv screen, and the recommended positions are set to different exposure times and positions for different viewer groups and different time periods, so as to achieve better recommending effects, the tv viewport recommended positions may be divided into top recommended positions, i.e. at the top of the tv screen, which are generally used for recommending the most important programs or advertisements, longer exposure times, side recommended positions, i.e. at the side of the tv screen, which are generally used for recommending the less important programs or advertisements, shorter exposure times, and bottom recommended positions, i.e. at the bottom of the tv screen, which are generally used for recommending some of the less important programs or advertisements, shorter exposure times, wherein the recommended positions refer to individual content units seen on the tv, each recommended position may be configured with a content resource, and the in-focus data indicates a status data of the cursor staying on each recommended position.
S200, weighting and giving processing to the characteristic data of the playing content to construct a television playing content reporting contribution value and a television playing content viewing contribution value;
it should be noted that, in some embodiments, as shown in fig. 5, step S200 may include: s201, determining the duty ratio data of the play content characteristic data in a preset period frequency according to the play content characteristic data; s202, determining weights corresponding to the playing content characteristic data, wherein the weights of the playing content characteristic data comprise television viewport recommendation bit exposure data weights, television viewport recommendation bit focus-falling data weights and user behavior data weights; s203, combining the weight of the playing content characteristic data and the duty ratio data of the playing content characteristic data to construct a television playing content reporting contribution value and a television playing content viewing contribution value.
In some embodiments, determining a preset period frequency, which may be a reasonable time span period, that is, representing one week or one month, or a time point dimension, that is, an early and late peak, and the like, further, in the preset period frequency, obtaining a total number of exposure times of all recommended position content viewports, a total number of exposure and focus falling times of all recommended position content viewports, a total number of exposure and click clicking times of all recommended position content viewports, a total number of viewing time of all content and a total number of content ordering, and dividing the television viewport recommended position exposure data, the television viewport recommended position focus falling data, the number of clicked times of television playing content, the television playing content viewing time data and the television playing content ordering times with the corresponding total number of times respectively to obtain duty ratio data related to the content, wherein the duty ratio data specifically comprises a television viewport recommended position exposure data duty ratio, a television viewport recommended position focus falling data duty ratio, a television playing content clicked time data duty ratio, and a television playing content ordering time duty ratio;
the calculation expression of the recommended bit exposure data duty ratio of the television viewing port is as follows:
In the above, age 1 Sigma N representing the recommended bit exposure data duty ratio of the television viewport 1 Indicating the total number of exposure times of all recommended bit content viewports, n 1 Indicating recommended bit exposure data for the television viewport.
The calculation expression of the television viewing port recommended bit focus-falling data ratio is as follows:
in the above, age 2 Representing the recommended bit focal data duty ratio of television viewing port, ΣN 2 Indicating total exposure times of all recommended position content view ports and n 2 And representing television viewport recommended bit focus-down data.
The calculated expression of the clicked times of the television playing content is as follows:
in the above, age 3 Representing the number of times the television broadcast content is clicked, ΣN 3 Indicating the total number of times of exposing and clicking the view port of all recommended bit contents, n 3 Indicating the number of times the television broadcast content has been clicked.
The calculation expression of the audience time length data duty ratio of the television broadcasting content is as follows:
in the above, age 4 Sigma N representing the duty cycle of the viewing duration data of the television broadcast content 4 Representing the total viewing time of all contents, n 4 And data representing the viewing time of the television broadcast content.
The computing expression of the order times of the television playing content is as follows:
in the above, age 5 Representing the order count of television broadcast content 5 Representing the total number of subscriptions to all content, n 5 Representing the number of orders for television broadcast content.
In some specific embodiments, the weight data of the embodiment of the invention can be dynamically configured and adjusted according to the interests of the user, firstly, the interests of the user are measured according to the television viewport recommended position exposure data duty ratio, the television viewport recommended position focus falling data duty ratio, the television playing content clicked time duty ratio, the television playing content viewing time length data duty ratio and the television playing content ordering time duty ratio, so as to obtain the interests of the user on different categories of television playing content, the corresponding weight is calculated for each playing content according to the interests of the user, the weight can be weighted average or given corresponding weight based on the interests of the user so as to reflect the interests of the user on different parameters, and the weights of the parameters are dynamically adjusted according to the interests of the user and real-time feedback. For example, if a user is more interested in a certain category of television broadcast content, the parameter weight of the commodity can be correspondingly increased to better meet the requirement of the user, the adjusted parameter weight is applied to an algorithm and a model to optimize the result of recommendation, search or other related tasks, the optimization can be realized by modifying the weight parameter in the algorithm or retraining the model, the performance of the system and the feedback of the user are continuously monitored, the parameter weight is adjusted according to the actual situation, if the system performance is poor or the user is not satisfied with the recommendation result, the setting of the parameter weight needs to be reviewed again, and the adjustment is correspondingly performed, so that the weight is given to the broadcast content characteristic data, wherein the weight result comprises the view port exposure recommendation bit occupation weight, and the view port exposure occupation ratio of the content is a coefficient in the contribution degree; the focal length of the recommended site of view port exposure is the focal length of the recommended site of view port exposure of the content; the user click content duty ratio weight refers to the coefficient of the content duty ratio in the contribution degree clicked by the user; the content viewing duration and the subscription source duty ratio weight refer to coefficients of the content in the contribution degree of the viewing duration and the subscription source duty ratio.
In some embodiments, the weight of the characteristic data of the playing content and the duty ratio data of the characteristic data of the playing content are combined to construct a television playing content reporting contribution value and a television playing content viewing contribution value, the television playing content reporting contribution value is used for knowing the preference degree of a user on different programs, which is helpful for better grasping the demands of the user, optimizing the program content and arrangement, improving the user satisfaction, the contribution value can be used as one of indexes of program quality evaluation, helping a system terminal to know the popularity degree and effect of the television program type, the contribution value can be used as one of reference indexes for predicting the viewing rate, the viewing trend of future programs can be predicted through analysis of historical contribution data, the program scheduling is better planned, the broadcasting strategy is helped to be better planned, the television playing content viewing contribution value is used for knowing the audience acceptance degree and the popularity degree of a certain type of television content, which programs have higher audience attention degree and viewing rate can be known through analysis on the viewing contribution degree of different programs, thereby selecting a more suitable advertisement strategy, and analyzing the historical contribution value data, the audience demand of the television program type can be better understood, the viewing trend of the future television content is better understood, and the television content is better understood by the audience demand of the television content is better planned through analysis of the audience demand of the television content and the television content;
The calculation expression of the contribution value of the television broadcasting content report is as follows:
E a ＝(Age 1 *P 1 +Age 2 *P 2 +Age 3 *P3 3 )*t
in the above, E a The value of contribution degree, age, of reporting television playing content 1 Representing electricityViewing port recommended bit exposure data duty ratio, age 2 Age represents the focal data duty ratio of the recommended position of the television viewing port 3 Representing the clicked times of the television playing content, P 1 Indicating the weight of the recommended bit exposure data of the television viewport, P 2 Representing the weight of the television viewport recommended bit focus-down data, P 3 The method comprises the steps of representing the clicked times weight of television playing content, and t represents preset periodic frequency;
the calculation expression of the television broadcast content audience rating contribution value is as follows:
E b ＝(Age 4 +Age 5 )*P 4 *t
in the above, E b Age representing audience contribution value of television broadcast content 4 Data duty ratio, age, representing viewing time of television broadcast content 5 Representing the ordering frequency of television playing content and P 4 The data weight of the television broadcast content viewing time length and the ordering frequency weight of the television broadcast content are represented, and t represents the preset cycle frequency.
In the embodiment of the present invention, P 1 +P 2 +P 3 +P 4 ＝100％。
S300, acquiring behavior data of watching content of a user, and determining a dynamic operation recommendation coefficient of the user;
it should be noted that, in some embodiments, as shown in fig. 6, step S300 may include: s301, collecting user watching content behavior data, wherein the user watching content behavior data comprises television content classification data, staff data and business type data; s302, performing data cleaning and re-processing on the user watching content behavior data to obtain preprocessed user watching content behavior data; s303, determining the duty ratio of the user watching content behavior data in a preset period frequency according to the preprocessed user watching content behavior data; s304, determining corresponding user watching content behavior data coefficients according to the user watching content behavior data duty ratio; s305, determining a dynamic operation recommendation coefficient of the user according to the ratio of the user watching content behavior data coefficient to the user watching content behavior data.
In some embodiments, behavior data of watching content of a user is collected, wherein the classification data of television content is a result of classifying and tagging television programs, and is mainly used for facilitating operations such as searching, browsing and recommending the television programs. Such classification data typically includes aspects of program type, topic, style, audience population, etc., and may be generated based on a variety of means such as manual classification, machine learning algorithms, etc. The actor data refers to data related to actors, guests, and moderators related to the television program. Such data may include information about the actors 'names, professions, performance experiences, lists of works, etc., as well as background information about the guests, the host's host style and experience, etc. Such data may assist the television station in selecting the appropriate actors and guests to manufacture the program, improving the quality and appeal of the program. The service type data refers to data related to television services, including the type of television channel, the cost of programming, advertising revenue, audience rating, etc. Such data may assist the television station in making business decisions and data analysis, such as scheduling programs, adjusting advertising strategies, assessing program quality and revenue, and the like. The embodiment of the invention can further and more accurately grasp the interest data type of the user and know the interest change of the user in real time by enriching the content behavior data watched by the user, thereby being beneficial to weight adjustment in the step S200.
In some embodiments, preprocessing is performed on the collected data, including data cleaning, missing value processing, outlier processing, etc., where the steps of this embodiment are mainly for improving the quality and accuracy of the data; after the data preprocessing, data deduplication processing is required. The steps of the specific embodiment are mainly used for removing repeated data records, so that interference to subsequent analysis is avoided; the data is standardized, and different types of data are subjected to normalization processing, so that the different types of data have comparability; after data normalization, data conversion may be performed to convert the data into a form suitable for machine learning algorithms for better user behavior analysis; the law and trend of watching the content by the user are found by mining the data after the duplication removal and conversion by using a machine learning algorithm, so that the behavior mode of the user is better understood; and analyzing the mined results to obtain the characteristics and the trend of the behavior of the user for watching the content so as to better understand the interests and the demands of the user.
In some embodiments, the user viewing content behavior data duty ratio in the preset period frequency is determined according to the preprocessed user viewing content behavior data, namely, the duty ratio comprises the television content classification data duty ratio, the staff data duty ratio and the service type data duty ratio.
In some embodiments, the corresponding user viewing content behavior data coefficients including an operation configuration content type recommendation coefficient, an operation configuration staffing recommendation coefficient, and an operation configuration business classification recommendation coefficient are determined according to the user viewing content behavior data duty ratio.
In some embodiments, the user dynamic operation recommendation coefficient is determined according to the ratio of the user viewing content behavior data coefficient to the user viewing content behavior data, and the user dynamic operation recommendation coefficient can evaluate the acceptance degree and satisfaction degree of the user on the recommended content and predict the future behavior and requirement of the user. The coefficient can be calculated and analyzed based on behavior data, preference, feedback and other related information of the user so as to help operators to better know user demands and behavior modes, optimize recommendation algorithms and strategies, improve user satisfaction and liveness, and the calculation expression of the user dynamic operation recommendation coefficient is as follows:
E c ＝Age a *P a +Age b *P b +Age c *P c
in the above, E c Representing the dynamic operation recommendation coefficient of the user, age a Representing the ratio of classified data of television content, age b Representing the duty ratio of the staff data, age c Representing the duty ratio of service type data, P a Representing operational configuration content type recommendation coefficient, P b Representing the recommendation coefficient of operators of operation configuration, P c And representing the operational configuration service classification recommendation coefficient.
In the embodiment of the present invention, P a +P b +P c ＝100％。
S400, carrying out weighted calculation processing on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient, and updating recommendation data of the television viewport exposure recommendation position according to a calculation result;
it should be noted that, in some embodiments, as shown in fig. 7, step S400 may include: s401, carrying out weighted calculation processing on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient to obtain a calculation result; s402, constructing a preset exposure coefficient threshold; s403, selecting television playing contents corresponding to which the calculation result is larger than the preset exposure coefficient threshold value, and updating recommended data of the television viewport exposure recommended bit.
In some embodiments, the contribution value of the television broadcast content, the audience contribution value of the television broadcast content and the dynamic operation recommendation coefficient of the user are weighted, an exposure coefficient threshold is set, the exposure coefficient threshold represents the interested degree of the user for exposing the content, a reference value can be set according to a specific actual scene, if the television content corresponding to the exposure coefficient threshold is higher than the exposure coefficient threshold, the television content corresponding to the exposure coefficient threshold is regarded as the interested content for the user, and if the television content corresponding to the television content lower than the exposure coefficient threshold is regarded as the user and is not fully interested in the content, the weight in the step S200 is further subjected to the random adjustment processing, so that recommendation of the television broadcast content according to the interest type change of the user is realized, recommendation data of the exposure recommendation bit of the television view port is updated, and the exposure coefficient of each television broadcast content is calculated according to related data and algorithm model of the television broadcast content. This coefficient may reflect the exposure and focus of the content in the television market; screening television broadcasting contents meeting the conditions, and screening television broadcasting contents with exposure coefficients larger than a preset exposure coefficient threshold according to the calculation result. The content may have higher exposure value and attention, and is suitable for further recommendation and popularization; and updating the recommendation data of the television viewport exposure recommendation bit, and updating the recommendation data of the television playing content meeting the conditions into the television viewport exposure recommendation bit. Such data may include program names, actor information, play times, program profiles, etc., to provide a user with a better understanding and selection of content of interest; and continuously monitoring and adjusting indexes such as click rate, viewing rate and the like of the television viewport exposure recommended bit after the recommended data are updated, and adjusting and optimizing a preset exposure coefficient threshold value and the recommended data according to actual conditions.
It should be noted that, when selecting television playing content with a calculation result greater than the preset exposure coefficient threshold, the embodiment of the invention further comprehensively considers the accuracy and stability of the data, avoids being affected by abnormal values and noise, and updates and adjusts the recommended data according to actual conditions so as to maintain the accuracy and instantaneity.
In summary, aiming at the related problems existing in the prior art, the embodiment of the invention provides an implementation manner which is helpful to improve the configuration efficiency and the hot spot updating speed and to improve the experience of the user according to the content pushed in real time according to the interest change of the user. The method comprises the steps of obtaining recommended data of a television viewport exposure recommendation position, carrying out data feature extraction processing, changing the existing point report into face report, expanding a user behavior data face, further obtaining interest types and non-interest types of a current user, perceiving and predicting behavior data of three users, improving the perception degree of the user, further carrying out weight giving processing on the played content feature data, constructing a television playing content report contribution value and a television playing content audience contribution value, determining a user dynamic operation recommendation coefficient, carrying out weight judgment on the number of times of exposure of the recommended position of a user browsing layout and the number of times of content focus falling of the user in the layout recommendation position, predicting the new content demand direction of the user, displaying a data stream of the new content by the new content, improving the configuration efficiency, increasing the speed of hot spot update, expanding the recommended content, carrying out content pushed in real time according to the interest change of the user, namely carrying out more accurate content recommendation by enriching the interest data types of the user, finally carrying out weight calculation processing on the television playing content report contribution value, the television playing content audience contribution value and the user dynamic operation recommendation coefficient, carrying out weight calculation updating on the recommendation content contribution value and the user dynamic operation recommendation coefficient, and carrying out timely display of the recommended content according to the recommendation content in a real-time operation layout, improving the recommendation content experience mode, and improving the user experience by combining the recommendation position and the recommendation operation window.
In another aspect, as shown in fig. 8, an embodiment of the present invention provides a push device 800 for playing content on a television, including: a first module 810, configured to obtain recommended data of a television viewport recommended bit and perform data feature extraction processing to obtain playing content feature data, where the playing content feature data includes the television viewport recommended bit exposure data, television viewport recommended bit focus-falling data, and user behavior data, and the user behavior data includes a number of times that television playing content is clicked, a number of times that television playing content is watched, and a number of times that television playing content is ordered; a second module 820, configured to perform weight assignment processing on the play content feature data, and construct a contribution value of television play content reporting and a contribution value of television play content viewing; a third module 830, configured to collect behavior data of viewing content of a user, and determine a dynamic operation recommendation coefficient of the user; and a fourth module 840, configured to perform weighted calculation processing on the contribution value of the report of the television broadcast content, the audience contribution value of the television broadcast content, and the dynamic operation recommendation coefficient of the user, and update recommendation data of the television viewport exposure recommendation bit according to a calculation result.
The content of the method embodiment of the invention is suitable for the device embodiment, the specific function of the device embodiment is the same as that of the method embodiment, and the achieved beneficial effects are the same as those of the method.
On the other hand, as shown in fig. 9, an embodiment of the present invention further provides an electronic device 900, which includes at least one processor 910, and at least one memory 920 for storing at least one program; take a processor 910 and a memory 920 as examples.
The processor 910 and the memory 920 may be connected by a bus or other means.
Memory 920 acts as a non-transitory computer readable storage medium that may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, memory 920 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some implementations, the memory 920 may optionally include memory located remotely from the processor, which may be connected to the device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The above described embodiments of the electronic device are merely illustrative, wherein the units described as separate components may or may not be physically separate, i.e. may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In particular, FIG. 10 schematically shows a block diagram of a computer system for implementing an electronic device of an embodiment of the invention.
It should be noted that, the computer system 1000 of the electronic device shown in fig. 10 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present invention.
As shown in fig. 10, the computer system 1000 includes a central processing unit 1001 (Central Processing Unit, CPU) which can execute various appropriate actions and processes according to a program stored in a Read-Only Memory 1002 (ROM) or a program loaded from a storage section 1008 into a random access Memory 1003 (Random Access Memory, RAM). In the random access memory 1003, various programs and data necessary for the system operation are also stored. The cpu 1001, the rom 1002, and the ram 1003 are connected to each other via a bus 1004. An Input/Output interface 1005 (i.e., an I/O interface) is also connected to bus 1004.
The following components are connected to the input/output interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output portion 1007 including a Cathode Ray Tube (CRT), a liquid crystal display (Liquid Crystal Display, LCD), and a speaker; a storage portion 1008 including a hard disk or the like; and a communication section 1009 including a network interface card such as a local area network card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The drive 1010 is also connected to the input/output interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like, is installed as needed in the drive 1010, so that a computer program read out therefrom is installed as needed in the storage section 1008.
In particular, the processes described in the various method flowcharts may be implemented as computer software programs according to embodiments of the invention. For example, embodiments of the present invention include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 1009, and/or installed from the removable medium 1011. The computer programs, when executed by the central processor 1001, perform the various functions defined in the system of the present invention.
It should be noted that, the computer readable medium shown in the embodiments of the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The content of the method embodiment of the invention is suitable for the system embodiment, the specific function of the system embodiment is the same as that of the method embodiment, and the achieved beneficial effects are the same as those of the method.
Another aspect of the embodiments of the present invention also provides a computer-readable storage medium storing a program that is executed by a processor to implement a method as before.
The content of the method embodiment of the invention is applicable to the computer readable storage medium embodiment, the functions of the computer readable storage medium embodiment are the same as those of the method embodiment, and the achieved beneficial effects are the same as those of the method.
Embodiments of the present invention also disclose a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions may be read from a computer-readable storage medium by a processor of a computer device, and executed by the processor, to cause the computer device to perform the foregoing method.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that although in the above detailed description several modules of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the invention. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present invention may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a touch terminal, or a network device, etc.) to perform the method according to the embodiments of the present invention.
In some alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flowcharts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed, and in which sub-operations described as part of a larger operation are performed independently.
Furthermore, while the invention is described in the context of functional modules, it should be appreciated that, unless otherwise indicated, one or more of the functions and/or features may be integrated in a single physical device and/or software module or may be implemented in separate physical devices or software modules. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be apparent to those skilled in the art from consideration of their attributes, functions and internal relationships. Accordingly, one of ordinary skill in the art can implement the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative and are not intended to be limiting upon the scope of the invention, which is to be defined in the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution apparatus, device, or apparatus, such as a computer-based apparatus, processor-containing apparatus, or other apparatus that can fetch the instructions from the instruction execution apparatus, device, or apparatus and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution apparatus, device, or apparatus.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium may even be paper or other suitable medium upon which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to 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 a memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means 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 present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
While the preferred embodiment of the present invention has been described in detail, the present invention is not limited to the embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and the equivalent modifications or substitutions are intended to be included in the scope of the present invention as defined in the appended claims.

Claims (10)

1. A push method for television broadcast content, comprising:
acquiring recommended data of a television viewing port recommended position, and performing data feature extraction processing to obtain playing content feature data, wherein the playing content feature data comprises the television viewing port recommended position exposed data, television viewing port recommended position focusing data and user behavior data, and the user behavior data comprises the clicked times of television playing content, television playing content viewing time length data and television playing content ordering times;
Weighting the characteristic data of the playing content to construct a television playing content reporting contribution value and a television playing content viewing contribution value;
collecting behavior data of watching content of a user, and determining a dynamic operation recommendation coefficient of the user;
and carrying out weighted calculation processing on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient, and updating recommendation data of the television viewport exposure recommendation bit according to a calculation result.
2. The method for pushing content played by a television according to claim 1, wherein the obtaining recommended data of the television viewport exposure recommended bit and performing data feature extraction processing to obtain the content played feature data comprises:
collecting recommendation data of a television viewport exposure recommendation bit;
cleaning and re-processing the recommended data of the television viewport exposure recommended bit to obtain the preprocessed recommended data of the television viewport exposure recommended bit;
and carrying out feature extraction processing based on the preprocessed recommended data of the television viewport exposure recommended bit to obtain the playing content feature data.
3. The method for pushing the television broadcast content according to claim 1, wherein the weighting the broadcast content feature data to construct a television broadcast content reporting contribution value and a television broadcast content viewing contribution value comprises:
Determining the duty ratio data of the play content characteristic data in the preset period frequency according to the play content characteristic data;
determining the weight corresponding to the playing content characteristic data, wherein the weight of the playing content characteristic data comprises a television viewing port recommended bit exposure data weight, a television viewing port recommended bit focus falling data weight and a user behavior data weight;
and combining the weight of the broadcasting content characteristic data and the duty ratio data of the broadcasting content characteristic data to construct the television broadcasting content reporting contribution value and the television broadcasting content audience contribution value.
4. The method for pushing content played by a television according to claim 3, wherein the calculation expression of the contribution value of the content played by a television is:
E a ＝(Age 1 *P 1 +Age 2 *P 2 +Age 3 *P 3 )*t
in the above, E a The value of contribution degree, age, of reporting television playing content 1 The recommended bit exposure data duty ratio of the television viewing port is represented, age 2 Age represents the focal data duty ratio of the recommended position of the television viewing port 3 Representing the clicked times of the television playing content, P 1 Indicating the weight of the recommended bit exposure data of the television viewport, P 2 Representing the weight of the television viewport recommended bit focus-down data, P 3 The weight of the clicked times of the television playing content is represented, and t represents the preset cycle frequency.
5. The method for pushing content for television broadcast according to claim 3, wherein the calculation expression of the audience contribution value of the content for television broadcast is:
E b ＝(Age 4 +Age 5 )*P 4 *t
in the above, E b Age representing audience contribution value of television broadcast content 4 Data duty ratio, age, representing viewing time of television broadcast content 5 Representing the ordering frequency of television playing content and P 4 Representing the content of a television broadcastThe data weight of the receiving time length and the ordering time weight of the television broadcasting content, and t represents the preset cycle frequency.
6. The method for pushing content played by a television according to claim 1, wherein the collecting behavior data of content watched by a user and determining a dynamic operation recommendation coefficient of the user comprise:
collecting user watching content behavior data, wherein the user watching content behavior data comprises television content classification data, staff data and business type data;
performing data cleaning and re-processing on the user watching content behavior data to obtain preprocessed user watching content behavior data;
determining the duty ratio of the user watching content behavior data in the preset period frequency according to the preprocessed user watching content behavior data;
Determining corresponding user viewing content behavior data coefficients according to the user viewing content behavior data duty ratio;
and determining the dynamic operation recommendation coefficient of the user according to the content watching behavior data coefficient of the user and the content watching behavior data duty ratio of the user.
7. The method for pushing the television broadcast content according to claim 1, wherein the weighting calculation is performed on the contribution value of the television broadcast content, the audience contribution value of the television broadcast content, and the dynamic operation recommendation coefficient of the user, and the recommendation data of the television viewport exposure recommendation bit is updated according to the calculation result, and the method comprises:
weighting calculation is carried out on the television broadcasting content reporting contribution value, the television broadcasting content viewing contribution value and the user dynamic operation recommendation coefficient to obtain a calculation result;
constructing a preset exposure coefficient threshold;
and selecting television broadcasting content corresponding to the calculated result larger than the preset exposure coefficient threshold value, and updating recommended data of the television viewport exposure recommended position.
8. A push device for television broadcast content, comprising:
The first module is used for acquiring recommended data of the television viewing port recommended bit and carrying out data feature extraction processing to obtain playing content feature data, wherein the playing content feature data comprises the television viewing port recommended bit exposure data, television viewing port recommended bit focusing data and user behavior data, and the user behavior data comprises the number of times that television playing content is clicked, television playing content viewing time length data and television playing content ordering number;
the second module is used for giving weight to the characteristic data of the playing content and constructing a television playing content reporting contribution value and a television playing content viewing contribution value;
the third module is used for collecting behavior data of the content watched by the user and determining a dynamic operation recommendation coefficient of the user;
and the fourth module is used for carrying out weighted calculation processing on the contribution value of the television broadcasting content, the audience contribution value of the television broadcasting content and the dynamic operation recommendation coefficient of the user, and updating recommendation data of the television viewport exposure recommendation bit according to a calculation result.
9. An electronic device comprising a processor and a memory;
the memory is used for storing programs;
The processor executing the program implements the method of any one of claims 1 to 7.
10. A computer storage medium in which a processor executable program is stored, characterized in that the processor executable program is for implementing the method according to any one of claims 1 to 7 when being executed by the processor.
CN202311690948.XA 2023-12-08 2023-12-08 Push method and device for television play content, electronic equipment and medium Pending CN117750093A (en)

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