Television permission recommendation method and device, storage medium and server

Abstract

The invention discloses a television permission recommendation method and device, a storage medium and a server, and relates to the technical field of the Internet, and the method comprises the steps: obtaining user feature data, a plurality of television permission packages and package combination strategy rules; performing authority plan combination analysis processing according to the user feature data, the multiple television authority plans and the plan combination strategy rule to obtain combination scores corresponding to multiple television authority plan combinations; according to the combination scores corresponding to the plurality of television permission package combinations, selecting a television permission package combination of which the combination score meets a predetermined condition from the plurality of television permission package combinations to obtain a to-be-recommended combination; and recommending the combination to be recommended. According to the application, appropriate television permission package combinations can be effectively recommended for different users, and the television use experience and the user selection utilization rate of the television permissions are improved.

Description

Technical Field

[0001] The present application relates to the field of Internet technology, and in particular to a method, device, storage medium and server for recommending television permissions. Background Art

[0002] Television (TV) is a device that is closely related to people's lives. Recommending appropriate TV permissions in TV has an important impact on people's TV usage experience. Among them, TV permissions include various TV viewing memberships (such as monthly movie memberships), various TV operation permissions, etc.

[0003] At present, in the related art, the way of recommending TV permissions in TV is usually to uniformly recommend several TV permissions configured by the operation team according to fixed rules for users to choose from. For example, several membership packages are recommended in TV for users to choose from.

[0004] Under the current approach, TV permission recommendations usually cannot effectively meet users' actual needs, resulting in the TV usage experience needing to be further improved and a low user selection rate for some TV permissions. Summary of the invention

[0005] The embodiment of the present application provides a television permission recommendation solution, which can effectively recommend appropriate television permissions, improve television usage experience and user selection and usage rate of television permissions.

[0006] The embodiments of the present application provide the following technical solutions:

[0007] According to one embodiment of the present application, a television permission recommendation method includes: obtaining user characteristic data, multiple television permission packages, and package combination policy rules; performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages, and the package combination policy rules to obtain combination scores corresponding to multiple television permission package combinations; according to the combination scores corresponding to the multiple television permission package combinations, selecting a television permission package combination whose combination score meets a predetermined condition from the multiple television permission package combinations to obtain a combination to be recommended; and recommending the combination to be recommended.

[0008] In some embodiments of the present application, the permission package combination analysis and processing is performed according to the user characteristic data, the multiple television permission packages, and the package combination strategy rules to obtain combination scores corresponding to the multiple television permission package combinations, including: taking each of the television permission package combinations as a candidate individual, performing genetic solution based on a genetic algorithm using the user characteristic data, the multiple television permission packages, and the package combination strategy rules to obtain fitness corresponding to multiple candidate individuals; and obtaining the combination score of the television permission package combination corresponding to each candidate individual according to the fitness corresponding to each of the candidate individuals.

[0009] In some embodiments of the present application, the genetic algorithm is based on the user feature data, the multiple television rights packages and the package combination strategy rules to perform genetic solving to obtain the fitness corresponding to multiple candidate individuals, including: generating an initial population based on the multiple television rights packages, the initial population including multiple initial individuals, wherein each of the initial individuals includes multiple television rights packages; according to the package combination strategy rules, using the user feature data and the package attributes of the television rights packages included in each of the initial individuals to perform fitness calculation to obtain the fitness of each of the initial individuals; according to the fitness of each of the initial individuals, the multiple initial individuals are selected and optimized to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals.

[0010] In some embodiments of the present application, the multiple initial individuals are selected and optimized according to the fitness of each of the initial individuals to obtain the multiple candidate individuals and the corresponding fitness of each of the candidate individuals, including: individual selection from the multiple initial individuals to obtain multiple parent individuals; crossover processing on the multiple parent individuals to obtain multiple offspring individuals; mutation operation on the multiple offspring individuals to obtain multiple mutant individuals; individual update of the initial population with the multiple mutant individuals to obtain an updated population; iteratively performing fitness calculation, individual selection, crossover processing, mutation operation and individual update on the updated population until the termination condition is met to obtain the multiple candidate individuals and the corresponding fitness.

[0011] In some embodiments of the present application, the fitness calculation is performed according to the package combination strategy rule using the user characteristic data and the package attributes of the TV permission packages included in each of the initial individuals to obtain the fitness of each of the initial individuals, including: for each of the initial individuals, calculating the matching score between the user characteristic data and the package attributes of each TV permission package included in the initial individual and the package combination strategy rule; determining the proportion of TV permission packages included in the initial individuals whose matching scores are higher than a predetermined threshold; and obtaining the fitness of the initial individuals based on the proportion.

[0012] In some embodiments of the present application, performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages, and the package combination policy rules to obtain combination scores corresponding to the multiple television permission package combinations includes: inputting the user characteristic data, the multiple television permission packages, and the package combination policy rules into a preset package combination analysis model to perform permission package combination analysis and processing to obtain combination scores corresponding to the multiple television permission package combinations.

[0013] In some embodiments of the present application, selecting a TV permission package combination whose combination score meets a predetermined condition from the multiple TV permission package combinations to obtain a combination to be recommended includes: selecting a TV permission package combination corresponding to a combination score ranked before a predetermined score from the multiple TV permission package combinations; and determining the TV permission package combination corresponding to the combination score ranked before the predetermined score as the combination to be recommended.

[0014] In some embodiments of the present application, the plurality of television permission packages include a plurality of different television movie viewing membership packages and / or a plurality of different television operation permission packages.

[0015] In some embodiments of the present application, the multiple television permission packages are determined in the following manner: obtaining permission requirement information in the target television; obtaining television permission packages matching the permission requirement information from a permission pool to obtain the multiple television permission packages.

[0016] According to one embodiment of the present application, a television permission recommendation device includes: an acquisition module, which is used to acquire user characteristic data, multiple television permission packages and package combination policy rules; an analysis module, which is used to perform permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages and the package combination policy rules, and obtain combination scores corresponding to multiple television permission package combinations; a selection module, which is used to select a television permission package combination whose combination score meets a predetermined condition from the multiple television permission package combinations according to the combination scores corresponding to the multiple television permission package combinations, and obtain a combination to be recommended; and a recommendation module, which is used to recommend the combination to be recommended.

[0017] In some embodiments of the present application, the analysis module is used to: take each of the TV rights package combinations as a candidate individual, perform genetic solution based on a genetic algorithm, use the user feature data, the multiple TV rights packages and the package combination strategy rules to obtain the fitness corresponding to the multiple candidate individuals; and obtain the combined score of the TV rights package combination corresponding to each of the candidate individuals according to the fitness corresponding to each of the candidate individuals.

[0018] In some embodiments of the present application, the analysis module is used to: generate an initial population based on the multiple television rights packages, the initial population including multiple initial individuals, wherein each of the initial individuals includes multiple television rights packages; according to the package combination strategy rules, use the user feature data and the package attributes of the television rights packages included in each of the initial individuals to perform fitness calculations to obtain the fitness of each of the initial individuals; based on the fitness of each of the initial individuals, perform selection optimization processing on the multiple initial individuals to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals.

[0019] In some embodiments of the present application, the analysis module is used to: select individuals from the multiple initial individuals to obtain multiple parent individuals; perform crossover processing on the multiple parent individuals to obtain multiple offspring individuals; perform mutation operations on the multiple offspring individuals to obtain multiple mutant individuals; perform individual update of the initial population using the multiple mutant individuals to obtain an updated population; iteratively perform fitness calculation, individual selection, crossover processing, mutation operations and individual updates on the updated population until the termination conditions are met, thereby obtaining the multiple candidate individuals and corresponding fitness.

[0020] In some embodiments of the present application, the analysis module is used to: calculate, for each of the initial individuals, a matching score between the user feature data and the package attributes of each television permission package included in the initial individual and the package combination strategy rules; determine a proportion of television permission packages included in the initial individuals whose matching scores are higher than a predetermined threshold; and obtain the fitness of the initial individual based on the proportion.

[0021] In some embodiments of the present application, the analysis module is used to: input the user feature data, the multiple television permission packages, and the package combination policy rules into a preset package combination analysis model to perform permission package combination analysis and processing, and obtain combination scores corresponding to multiple television permission package combinations.

[0022] In some embodiments of the present application, the selection module is used to: select a TV permission package combination corresponding to a combination score ranked before a predetermined score from the multiple TV permission package combinations; and determine the TV permission package combination corresponding to the combination score ranked before the predetermined score as the combination to be recommended.

[0023] In some embodiments of the present application, the plurality of television permission packages include a plurality of different television movie viewing membership packages and / or a plurality of different television operation permission packages.

[0024] In some embodiments of the present application, the multiple television permission packages are determined in the following manner: obtaining permission requirement information in the target television; obtaining television permission packages matching the permission requirement information from a permission pool to obtain the multiple television permission packages.

[0025] According to another embodiment of the present application, a storage medium stores a computer program thereon, and when the computer program is executed by a processor of a server, the computer executes the method described in the embodiment of the present application.

[0026] According to another embodiment of the present application, a server may include: a memory storing a computer program; and a processor reading the computer program stored in the memory to execute the method described in the embodiment of the present application.

[0027] According to another embodiment of the present application, a computer program product or a computer program includes a computer instruction stored in a computer-readable storage medium. A processor of a server reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the server executes the method provided in various optional implementations described in the embodiments of the present application.

[0028] In an embodiment of the present application, user characteristic data, multiple television permission packages, and package combination policy rules are obtained; permission package combination analysis and processing are performed based on the user characteristic data, the multiple television permission packages, and the package combination policy rules to obtain combination scores corresponding to multiple television permission package combinations; based on the combination scores corresponding to the multiple television permission package combinations, a television permission package combination whose combination score meets a predetermined condition is selected from the multiple television permission package combinations to obtain a combination to be recommended; and the combination to be recommended is recommended.

[0029] In this way, permission package combination analysis and processing is performed according to user feature data, multiple TV permission packages and package combination strategy rules to obtain combination scores corresponding to multiple TV permission package combinations, and then, a TV permission package combination whose combination score meets predetermined conditions is selected from the multiple TV permission package combinations to obtain a to-be-recommended combination, and the to-be-recommended combination is recommended, so that suitable TV permission package combinations can be effectively recommended for different users, thereby improving TV usage experience and user selection and usage rate of TV permissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 A flowchart of a method for recommending television permissions according to an embodiment of the present application is shown.

[0032] Figure 2 A genetic solution flow chart according to an embodiment of the present application is shown.

[0033] Figure 3 A selection optimization flow chart according to an embodiment of the present application is shown.

[0034] Figure 4 A block diagram of a television permission recommendation device according to an embodiment of the present application is shown.

[0035] Figure 5 A block diagram of a server according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0036] The present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the embodiments provided herein are only used to explain the present disclosure and are not intended to limit the present disclosure. In addition, the embodiments provided below are partial embodiments for implementing the present disclosure, rather than providing all embodiments for implementing the present disclosure. In the absence of conflict, the technical solutions recorded in the embodiments of the present disclosure can be implemented in any combination.

[0037] It should be noted that, in the embodiments of the present disclosure, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a method or apparatus including a series of elements includes not only the elements explicitly recorded, but also includes other elements not explicitly listed, or also includes elements inherent to the implementation of the method or apparatus. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other related elements in the method or apparatus including the element (such as a step in the method or a unit in the apparatus, for example, a unit may be a part of a circuit, a part of a processor, a part of a program or software, etc.).

[0038] For example, the TV permission recommendation method provided in the embodiment of the present disclosure includes a series of steps, but the TV permission recommendation method provided in the embodiment of the present disclosure is not limited to the recorded steps. Similarly, the TV permission recommendation device provided in the embodiment of the present disclosure includes a series of units, but the device provided in the embodiment of the present disclosure is not limited to including the units explicitly recorded, and can also include units required to obtain relevant information or perform processing based on the information.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present disclosure belongs. The terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0040] It is understandable that in the specific implementation of this application, related data such as user feature data is involved. When the embodiments in this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0041] Figure 1The flowchart of the method for recommending TV permissions according to an embodiment of the present application is schematically shown. The execution subject of the method for recommending TV permissions can be any server with processing capabilities, such as a terminal or a server, a terminal such as a TV itself, a computer, a mobile phone, a smart watch, and a home appliance, and a server such as a cloud server or a physical server.

[0042] like Figure 1 As shown, the television authority recommendation method may include steps S110 to S140.

[0043] Step S110, obtaining user characteristic data, multiple television permission packages and package combination policy rules; Step S120, performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages and the package combination policy rules, and obtaining combination scores corresponding to multiple television permission package combinations; Step S130, selecting a television permission package combination whose combination score meets a predetermined condition from the multiple television permission package combinations according to the combination scores corresponding to the multiple television permission package combinations, and obtaining a combination to be recommended; Step S140, recommending the combination to be recommended.

[0044] User characteristic data refers to the relevant characteristic data of users who use the television. For example, for television A, user characteristic data of users who use television A can be obtained, and for television B, user characteristic data of users who use television B can be obtained. User characteristic data may include, but is not limited to, one or more of user attributes (such as age, gender, etc.), permission selection and use history data (such as historically purchased film and television memberships or used television operation permissions, etc.), behavior data (such as film and television viewing history data), and tag information (such as user type tags).

[0045] A TV permission package is a package of TV permissions. Various TV permission packages may include a variety of different TV movie viewing membership packages (for example, A movie membership package, B movie membership package, etc.) and / or a variety of different TV operation permission packages (for example, A game permission package, B game permission package, face recognition unlocking permission package, voice control permission package, etc.).

[0046] The package combination strategy rules are the relevant combination strategy rules for TV rights packages. The package combination strategy rules are usually some combination strategy rules related to TV rights packages configured by the operation personnel of the TV manufacturer according to some operation requirements. The package combination strategy rules may include but are not limited to package issuance rules, package purchase limit rules, user diversion rules, etc.

[0047] The server can obtain user feature data, multiple TV permission packages, and package combination policy rules from a specified location. Then, according to the user feature data, multiple TV permission packages, and package combination policy rules, permission package combination analysis and processing are performed to obtain combination scores corresponding to multiple TV permission package combinations, wherein each TV permission package combination includes multiple TV permission packages, and the multiple TV permission packages in different TV permission package combinations are partially different or completely different.

[0048] The higher the combination score of a certain TV permission package combination, the higher the degree of mutual adaptation of the TV permission package combination with the user using the TV and the package combination policy rules. According to the combination scores corresponding to the multiple TV permission package combinations, a TV permission package combination whose combination score meets the predetermined conditions is selected from the multiple TV permission package combinations to obtain a combination to be recommended.

[0049] The combination to be recommended is recommended. For example, multiple TV permission packages included in the combination to be recommended can be combined into a package list and displayed on the target TV. The target TV is the TV logged in by the user matching the user feature data. For example, the users matching the user feature data of A include user 1 and user 2, and the package list can be recommended and displayed on TV 1 and TV 2 logged in by user 1 and user 2.

[0050] In this way, permission package combination analysis and processing is performed according to user feature data, multiple TV permission packages and package combination strategy rules to obtain combination scores corresponding to multiple TV permission package combinations, and then, a TV permission package combination whose combination score meets predetermined conditions is selected from the multiple TV permission package combinations to obtain a to-be-recommended combination, and the to-be-recommended combination is recommended, so that suitable TV permission package combinations can be effectively recommended for different users, thereby improving TV usage experience and user selection and usage rate of TV permissions.

[0051] Described below Figure 1 When recommending TV permissions under the embodiment, further optional specific embodiments are provided under each step performed.

[0052] In one embodiment, the multiple television permission packages described in the embodiment of the present application include multiple different television movie viewing membership packages and / or multiple different television operation permission packages.

[0053] A TV permission package is a package of TV permissions. Multiple TV permission packages may include multiple different candidate TV movie viewing membership packages (such as A movie membership package, B movie membership package, etc.) and / or multiple different TV operation permission packages (such as A game permission package, B game permission package, face recognition unlocking permission package, voice control permission package, etc.).

[0054] In one embodiment of the present application, the multiple TV permission packages include multiple different TV viewing membership packages. In another embodiment of the present application, the multiple TV permission packages only include multiple different TV operation permission packages. In another embodiment of the present application, the multiple TV permission packages include both multiple different TV operation permission packages and multiple different TV viewing membership packages.

[0055] Furthermore, in an embodiment, when acquiring the multiple television permission packages, all television permission packages preset in the permission pool may be used as the multiple television permission packages.

[0056] Further, in one embodiment, the multiple television permission packages are determined in the following manner: obtaining permission requirement information in the target television; obtaining television permission packages matching the permission requirement information from a permission pool to obtain the multiple television permission packages.

[0057] In this embodiment, for the target TV, firstly, the permission requirement information in the target TV is obtained, and the TV permission packages matching the permission requirement information are obtained from the permission pool to obtain multiple TV permission packages, and the combination to be recommended can be further determined according to the multiple TV permission packages matching the permission requirement information, so as to further improve the TV permission recommendation effect. Among them, the permission requirement information in the target TV can be input by the user through voice or interface.

[0058] In one embodiment, performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages, and the package combination policy rules to obtain combination scores corresponding to the multiple television permission package combinations may include: inputting the user characteristic data, the multiple television permission packages, and the package combination policy rules into a preset package combination analysis model to perform permission package combination analysis and processing to obtain combination scores corresponding to the multiple television permission package combinations.

[0059] The preset package combination analysis model can be a model obtained by fine-tuning the existing large model or a model obtained by training other networks such as a convolutional upscaling network. User feature data, multiple TV rights packages, and package combination strategy rules are input into the preset package combination analysis model for rights package combination analysis and processing, so that the combination scores corresponding to multiple TV rights package combinations can be obtained efficiently and reliably.

[0060] Further, in an embodiment, performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages, and the package combination strategy rules to obtain combination scores corresponding to the multiple television permission package combinations includes:

[0061] Each of the television rights package combinations is taken as a candidate individual, and based on a genetic algorithm, a genetic solution is performed using the user feature data, the multiple television rights packages and the package combination strategy rules to obtain the fitness corresponding to the multiple candidate individuals; based on the fitness corresponding to each of the candidate individuals, a combination score of the television rights package combination corresponding to each of the candidate individuals is obtained.

[0062] Genetic Algorithm (GA) is an evolutionary algorithm for optimization problems, which finds the optimal solution by simulating natural selection and genetic mechanisms. The applicant has found that by taking each TV rights package combination as a candidate individual, using user feature data, multiple TV rights packages and package combination strategy rules for genetic solution based on a genetic algorithm, the fitness corresponding to multiple candidate individuals can be further obtained at low cost and high interpretability. The fitness of these multiple candidate individuals as a combined score can effectively reflect the quality of the multiple candidate individuals obtained through genetic optimization combination.

[0063] According to the fitness (i.e., a combination score), candidate individuals that meet the predetermined conditions can be selected from the multiple candidate individuals as a combination to be recommended. Combining and recommending the TV rights packages included in the combination to be recommended can further effectively recommend a suitable TV rights package combination to the user, further improving the TV usage experience and the user selection and utilization rate of TV rights.

[0064] In one embodiment, see Figure 2 The method of performing genetic solution based on a genetic algorithm using the user feature data, the multiple television rights packages, and the package combination strategy rules to obtain the fitness corresponding to multiple candidate individuals may specifically include:

[0065] Step S210, generating an initial population based on the multiple TV rights packages, the initial population including multiple initial individuals, wherein each of the initial individuals includes multiple TV rights packages; Step S220, performing fitness calculation according to the package combination strategy rules using the user feature data and the package attributes of the TV rights packages included in each of the initial individuals to obtain the fitness of each of the initial individuals; Step S230, performing selection optimization processing on the multiple initial individuals according to the fitness of each of the initial individuals to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals.

[0066] Based on a plurality of television rights packages, packages may be randomly combined to generate an initial population, the initial population including a plurality of initial individuals, wherein each initial individual includes a plurality of television rights packages, and television rights packages in different initial individuals may be partially or completely different.

[0067] Based on the preset fitness function, fitness calculation can be performed according to the package combination strategy rules using user feature data and the package attributes of the TV rights package included in each initial individual to obtain the fitness of each initial individual. The fitness of each initial individual is also the quality of the package combination formed by multiple TV rights packages in each initial individual.

[0068] Furthermore, according to the fitness of each initial individual, multiple initial individuals are selected and optimized, and finally the optimal solution is found by simulating natural selection and genetic mechanism to obtain multiple candidate individuals and the corresponding fitness of each candidate individual.

[0069] Further, the fitness calculation is performed using the user characteristic data and the package attributes of the TV authority package included in each of the initial individuals according to the package combination strategy rule to obtain the fitness of each of the initial individuals, which may specifically include:

[0070] For each of the initial individuals, the matching scores of the user feature data and the package attributes of each television authority package included in the initial individual and the package combination strategy rules are calculated; the proportion of television authority packages included in the initial individuals whose matching scores are higher than a predetermined threshold is determined; and the fitness of the initial individual is obtained according to the proportion.

[0071] Based on the preset fitness function, for each initial individual, the matching scores between the user characteristic data and the package attributes of each TV authority package included in the initial individual and the package combination strategy rule can be calculated, wherein the package attribute can be, for example, membership type, distribution strategy, price, term type, purchase restriction rule, etc. For example, the initial individual A includes TV authority packages 1, 2, ..., n, and the matching score 1 between the user characteristic data and TV authority package 1 and the package combination strategy rule, the matching score 2 between the user characteristic data and TV authority package 2 and the package combination strategy rule, ..., and the matching score n between the user characteristic data and TV authority package n and the package combination strategy rule can be calculated.

[0072] Furthermore, the proportion of TV rights packages with matching scores higher than a predetermined threshold included in the initial individuals can be statistically determined, and the fitness of the initial individuals can be obtained according to the proportion. For example, for initial individual A, the number of TV rights packages with matching scores higher than a predetermined threshold corresponding to initial individual A can be determined to be s, and thus the proportion is s / n. Based on the proportion, initial individual A can be further scored to obtain the fitness of initial individual A, wherein different proportions are predetermined to have corresponding fitness.

[0073] For further information, see Figure 3, performing selection optimization processing on the multiple initial individuals according to the fitness of each of the initial individuals to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals may specifically include:

[0074] Step S310, selecting individuals from the multiple initial individuals to obtain multiple parent individuals; step S320, performing crossover processing on the multiple parent individuals to obtain multiple offspring individuals; step S330, performing mutation operation on the multiple offspring individuals to obtain multiple mutant individuals; step S340, performing individual update of the initial population with the multiple mutant individuals to obtain an updated population; step S350, iteratively performing fitness calculation, individual selection, crossover processing, mutation operation and individual update on the updated population until the end condition is met, thereby obtaining the multiple candidate individuals and corresponding fitness.

[0075] Specifically, using the roulette wheel selection method for individual selection, individuals can be selected from multiple initial individuals, and the selected initial individuals are used as multiple parent individuals. Further, a multi-point crossover method can be used for crossover processing, and some genes (i.e., TV rights packages) of two parent individuals are exchanged, and the multiple parent individuals after the gene exchange are multiple mutant individuals. Further, some genes of the mutant individuals can be randomly changed with a certain probability through mutation operation, thereby obtaining multiple mutant individuals.

[0076] Multiple mutant individuals can be added to the initial population and some initial individuals with low fitness in the initial population can be removed, so as to update the individuals of the initial population and obtain an updated population with richer diversity. The fitness calculation, individual selection, crossover processing, mutation operation and individual update in the above steps are iteratively performed on the updated population until the end condition is met (for example, a predetermined number of iterations or fitness threshold is reached). The final population can include multiple candidate individuals and the fitness corresponding to each candidate individual can be obtained.

[0077] Further, in one embodiment, selecting a television authority package combination whose combination score meets a predetermined condition from the plurality of television authority package combinations to obtain a combination to be recommended includes:

[0078] Selecting a television authority package combination corresponding to a combination score before a predetermined score ranking from the multiple television authority package combinations; and determining the television authority package combination corresponding to the combination score before the predetermined score ranking as the to-be-recommended combination.

[0079] Each TV permission package combination can obtain a corresponding combination score, and a TV permission package combination corresponding to a combination score that is before a predetermined score ranking is selected from multiple TV permission package combinations, wherein the predetermined score ranking can be set according to actual needs, for example, if the predetermined score ranking is 2, a TV permission package combination with the highest score ranking can be finally obtained. The TV permission package combination corresponding to the combination score that is before the predetermined score ranking is determined as a combination to be recommended and recommended in the target TV, which can effectively recommend a suitable TV permission package combination to the corresponding user of the target TV, thereby improving the TV usage experience and the user selection and utilization rate of TV permissions.

[0080] In order to better implement the TV permission recommendation method provided in the embodiment of the present application, the embodiment of the present application also provides a TV permission recommendation device based on the TV permission recommendation method. The meanings of the terms are the same as those in the TV permission recommendation method, and the specific implementation details can refer to the description in the method embodiment. Figure 4 A block diagram of a television permission recommendation device according to an embodiment of the present application is shown.

[0081] like Figure 4 As shown, the television permission recommendation device 400 may include: an acquisition module 410 can be used to acquire user characteristic data, multiple television permission packages and package combination policy rules; an analysis module 420 can be used to perform permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages and the package combination policy rules to obtain combination scores corresponding to multiple television permission package combinations; a selection module 430 can be used to select a television permission package combination whose combination score meets predetermined conditions from the multiple television permission package combinations according to the combination scores corresponding to the multiple television permission package combinations to obtain a combination to be recommended; and a recommendation module 440 can be used to recommend the combination to be recommended.

[0082] In some embodiments of the present application, the analysis module is used to: take each of the TV rights package combinations as a candidate individual, perform genetic solution based on a genetic algorithm, use the user feature data, the multiple TV rights packages and the package combination strategy rules to obtain the fitness corresponding to the multiple candidate individuals; and obtain the combined score of the TV rights package combination corresponding to each of the candidate individuals according to the fitness corresponding to each of the candidate individuals.

[0083] In some embodiments of the present application, the analysis module is used to: generate an initial population based on the multiple television rights packages, the initial population including multiple initial individuals, wherein each of the initial individuals includes multiple television rights packages; according to the package combination strategy rules, use the user feature data and the package attributes of the television rights packages included in each of the initial individuals to perform fitness calculations to obtain the fitness of each of the initial individuals; based on the fitness of each of the initial individuals, perform selection optimization processing on the multiple initial individuals to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals.

[0084] In some embodiments of the present application, the analysis module is used to: select individuals from the multiple initial individuals to obtain multiple parent individuals; perform crossover processing on the multiple parent individuals to obtain multiple offspring individuals; perform mutation operations on the multiple offspring individuals to obtain multiple mutant individuals; perform individual update of the initial population using the multiple mutant individuals to obtain an updated population; iteratively perform fitness calculation, individual selection, crossover processing, mutation operations and individual updates on the updated population until the termination conditions are met, thereby obtaining the multiple candidate individuals and corresponding fitness.

[0085] In some embodiments of the present application, the analysis module is used to: calculate, for each of the initial individuals, a matching score between the user feature data and the package attributes of each television permission package included in the initial individual and the package combination strategy rules; determine a proportion of television permission packages included in the initial individuals whose matching scores are higher than a predetermined threshold; and obtain the fitness of the initial individual based on the proportion.

[0086] In some embodiments of the present application, the analysis module is used to: input the user feature data, the multiple television permission packages, and the package combination policy rules into a preset package combination analysis model to perform permission package combination analysis and processing, and obtain combination scores corresponding to multiple television permission package combinations.

[0087] In some embodiments of the present application, the selection module is used to: select a TV permission package combination corresponding to a combination score ranked before a predetermined score from the multiple TV permission package combinations; and determine the TV permission package combination corresponding to the combination score ranked before the predetermined score as the combination to be recommended.

[0088] In some embodiments of the present application, the plurality of television permission packages include a plurality of different television movie viewing membership packages and / or a plurality of different television operation permission packages.

[0089] In some embodiments of the present application, the multiple television permission packages are determined in the following manner: obtaining permission requirement information in the target television; obtaining television permission packages matching the permission requirement information from a permission pool to obtain the multiple television permission packages.

[0090] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0091] In addition, the present application also provides a server, such as Figure 5 As shown, Figure 5 A block diagram of a server according to an embodiment of the present application is shown, specifically:

[0092] The server may include one or more processors 501 of processing cores, one or more computer-readable storage media memories 502, power supplies 503 and other components. Those skilled in the art will appreciate that Figure 5 The server structure shown in the figure does not constitute a limitation on the server, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0093] The processor 501 is the control center of the server, and uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and / or modules stored in the memory 502, and calling data stored in the memory 502, the processor 501 performs various functions of the computer device and processes data, thereby monitoring the server as a whole. Optionally, the processor 501 may include one or more processing cores; preferably, the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user pages and application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 501.

[0094] The memory 502 can be used to store software programs and modules. The processor 501 executes various functional applications and data processing by running the software programs and modules stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 502 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 502 may also include a memory controller to provide the processor 501 with access to the memory 502.

[0095] The server also includes a power supply 503 for supplying power to each component. Preferably, the power supply 503 can be logically connected to the processor 501 through a power management system, so as to manage charging, discharging, power consumption and other functions through the power management system. The power supply 503 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0096] Although not shown, the server may also include a display unit, etc., which will not be described in detail here. Specifically in this embodiment, the processor 501 in the server will load the executable file corresponding to the process of one or more computer programs into the memory 502 according to the following instructions, and the processor 501 will run the computer program stored in the memory 502, so as to realize various functions in the aforementioned embodiments of the present application, such as the processor 501 can perform the following steps:

[0097] Acquire user characteristic data, multiple television permission packages, and package combination policy rules; perform permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages, and the package combination policy rules to obtain combination scores corresponding to multiple television permission package combinations; select, according to the combination scores corresponding to the multiple television permission package combinations, a television permission package combination whose combination score meets a predetermined condition from the multiple television permission package combinations to obtain a combination to be recommended; and perform combination recommendation on the television permission packages included in the combination to be recommended.

[0098] In some embodiments of the present application, the permission package combination analysis and processing is performed according to the user characteristic data, the multiple television permission packages, and the package combination strategy rules to obtain combination scores corresponding to the multiple television permission package combinations, including: taking each of the television permission package combinations as a candidate individual, performing genetic solution based on a genetic algorithm using the user characteristic data, the multiple television permission packages, and the package combination strategy rules to obtain fitness corresponding to multiple candidate individuals; and obtaining the combination score of the television permission package combination corresponding to each candidate individual according to the fitness corresponding to each of the candidate individuals.

[0099] In some embodiments of the present application, the genetic algorithm is based on the user feature data, the multiple television rights packages and the package combination strategy rules to perform genetic solving to obtain the fitness corresponding to multiple candidate individuals, including: generating an initial population based on the multiple television rights packages, the initial population including multiple initial individuals, wherein each of the initial individuals includes multiple television rights packages; according to the package combination strategy rules, using the user feature data and the package attributes of the television rights packages included in each of the initial individuals to perform fitness calculation to obtain the fitness of each of the initial individuals; according to the fitness of each of the initial individuals, the multiple initial individuals are selected and optimized to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals.

[0100] In some embodiments of the present application, the multiple initial individuals are selected and optimized according to the fitness of each of the initial individuals to obtain the multiple candidate individuals and the corresponding fitness of each of the candidate individuals, including: individual selection from the multiple initial individuals to obtain multiple parent individuals; crossover processing on the multiple parent individuals to obtain multiple offspring individuals; mutation operation on the multiple offspring individuals to obtain multiple mutant individuals; individual update of the initial population with the multiple mutant individuals to obtain an updated population; iteratively performing fitness calculation, individual selection, crossover processing, mutation operation and individual update on the updated population until the termination condition is met to obtain the multiple candidate individuals and the corresponding fitness.

[0101] In some embodiments of the present application, the fitness calculation is performed according to the package combination strategy rule using the user characteristic data and the package attributes of the TV permission packages included in each of the initial individuals to obtain the fitness of each of the initial individuals, including: for each of the initial individuals, calculating the matching score between the user characteristic data and the package attributes of each TV permission package included in the initial individual and the package combination strategy rule; determining the proportion of TV permission packages included in the initial individuals whose matching scores are higher than a predetermined threshold; and obtaining the fitness of the initial individuals based on the proportion.

[0102] In some embodiments of the present application, performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages, and the package combination policy rules to obtain combination scores corresponding to the multiple television permission package combinations includes: inputting the user characteristic data, the multiple television permission packages, and the package combination policy rules into a preset package combination analysis model to perform permission package combination analysis and processing to obtain combination scores corresponding to the multiple television permission package combinations.

[0103] In some embodiments of the present application, according to the combination scores corresponding to the multiple TV permission package combinations, selecting a TV permission package combination whose combination score meets a predetermined condition from the multiple TV permission package combinations to obtain a combination to be recommended, includes: selecting a TV permission package combination corresponding to a combination score ranked before a predetermined score from the multiple TV permission package combinations; and determining the TV permission package combination corresponding to the combination score ranked before the predetermined score as the combination to be recommended.

[0104] In some embodiments of the present application, the plurality of television permission packages include a plurality of different television movie viewing membership packages and / or a plurality of different television operation permission packages.

[0105] In some embodiments of the present application, the multiple television permission packages are determined in the following manner: obtaining permission requirement information in the target television; obtaining television permission packages matching the permission requirement information from a permission pool to obtain the multiple television permission packages.

[0106] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by a computer program, or by controlling related hardware through a computer program. The computer program may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0107] To this end, an embodiment of the present application further provides a storage medium, in which a computer program is stored. The computer program can be loaded by a processor to execute the steps in any method provided in the embodiment of the present application.

[0108] The storage medium may be a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0109] Since the computer program stored in the storage medium can execute the steps in any method provided in the embodiments of the present application, the beneficial effects that can be achieved by the method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0110] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0111] It should be understood that the present application is not limited to the embodiments that have been described above and shown in the accompanying drawings, but various modifications and changes may be made without departing from the scope thereof.

Claims

1. A method for recommending television permissions, characterized in that: include: Obtain user feature data, multiple TV rights packages, and package combination strategy rules; Performing permission package combination analysis and processing according to the user feature data, the multiple television permission packages, and the package combination strategy rules to obtain combination scores corresponding to the multiple television permission package combinations; Selecting a TV authority package combination whose combination score meets a predetermined condition from the multiple TV authority package combinations to obtain a combination to be recommended; The combination to be recommended is recommended.

2. The method according to claim 1, characterized in that The performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages and the package combination strategy rule to obtain combination scores corresponding to the multiple television permission package combinations includes: Taking each of the TV rights package combinations as a candidate individual, performing genetic solution based on a genetic algorithm using the user feature data, the multiple TV rights packages and the package combination strategy rules, and obtaining the fitness corresponding to the multiple candidate individuals; According to the fitness corresponding to each of the candidate individuals, a combination score of the television authority package combination corresponding to each of the candidate individuals is obtained.

3. The method according to claim 2, characterized in that The method of performing genetic solution based on a genetic algorithm using the user feature data, the multiple television authority packages, and the package combination strategy rules to obtain fitness corresponding to multiple candidate individuals includes: generating an initial population based on the multiple television authority packages, wherein the initial population includes multiple initial individuals, wherein each of the initial individuals includes multiple television authority packages; According to the package combination strategy rule, the user characteristic data and the package attributes of the television authority package included in each of the initial individuals are used to perform fitness calculation to obtain the fitness of each of the initial individuals; According to the fitness of each of the initial individuals, the multiple initial individuals are selected and optimized to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals.

4. The method according to claim 3, characterized in that The step of performing selection optimization processing on the multiple initial individuals according to the fitness of each of the initial individuals to obtain the multiple candidate individuals and the fitness corresponding to each of the candidate individuals includes: Selecting individuals from the multiple initial individuals to obtain multiple parent individuals; Performing crossover processing on the multiple parent individuals to obtain multiple offspring individuals; Performing mutation operation on the multiple offspring individuals to obtain multiple mutant individuals; Using the multiple mutant individuals to perform individual updates on the initial population to obtain an updated population; The updated population is iteratively subjected to fitness calculation, individual selection, crossover processing, mutation operation and individual updating until an end condition is met, thereby obtaining the plurality of candidate individuals and corresponding fitness.

5. The method according to claim 3, characterized in that: The step of calculating the fitness of each of the initial individuals using the user characteristic data and the package attributes of the television authority package included in each of the initial individuals according to the package combination strategy rule to obtain the fitness of each of the initial individuals includes: For each of the initial individuals, calculating a matching score between the user feature data and the package attributes of each television authority package included in the initial individual and the package combination strategy rule; determining a proportion of television entitlement packages included in the initial individuals and having a matching score above a predetermined threshold; According to the ratio, the fitness of the initial individual is obtained.

6. The method according to claim 1, characterized in that The performing permission package combination analysis and processing according to the user characteristic data, the multiple television permission packages and the package combination strategy rule to obtain combination scores corresponding to the multiple television permission package combinations includes: The user characteristic data, the multiple television permission packages and the package combination policy rules are input into a preset package combination analysis model to perform permission package combination analysis and processing, so as to obtain combination scores corresponding to the multiple television permission package combinations.

7. The method according to claim 1, characterized in that The step of selecting a television authority package combination whose combination score meets a predetermined condition from the plurality of television authority package combinations to obtain a combination to be recommended includes: Selecting a television rights package combination corresponding to a combination score that is before a predetermined score ranking from the plurality of television rights package combinations; The television authority package combination corresponding to the combination score that is before the predetermined score ranking is determined as the combination to be recommended.

8. The method according to any one of claims 1 to 7, characterized in that: The multiple television authority packages include multiple different television viewing membership packages and / or multiple different television operation authority packages.

9. The method according to claim 8, characterized in that The multiple TV rights packages are determined in the following manner: Obtain permission requirement information from the target TV; A television permission package matching the permission requirement information is acquired from a permission pool to obtain the multiple television permission packages.

10. A television authority recommendation device, characterized in that: include: An acquisition module is used to acquire user feature data, multiple TV permission packages, and package combination strategy rules; An analysis module, configured to perform analysis and processing of a combination of rights packages according to the user characteristic data, the multiple television rights packages, and the package combination strategy rules, and obtain combination scores corresponding to the multiple television rights package combinations; A selection module, configured to select, according to the combination scores corresponding to the plurality of television authority package combinations, a television authority package combination whose combination score meets a predetermined condition from the plurality of television authority package combinations, to obtain a combination to be recommended; The recommendation module is used to recommend the combination to be recommended.

11. A storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor at the server end, the computer is enabled to execute the method according to any one of claims 1 to 9.

12. A server, characterized in that: include: a memory storing a computer program; A processor reads a computer program stored in a memory to execute the method according to any one of claims 1 to 9.

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