CN116233495A - Program resource recommendation method and device, program management engine and storage medium - Google Patents

Program resource recommendation method and device, program management engine and storage medium Download PDF

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Publication number
CN116233495A
CN116233495A CN202111479456.7A CN202111479456A CN116233495A CN 116233495 A CN116233495 A CN 116233495A CN 202111479456 A CN202111479456 A CN 202111479456A CN 116233495 A CN116233495 A CN 116233495A
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Prior art keywords
resource
target
resource set
recommended
program
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黄志超
刘鹏
谢纯定
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Shenzhen Coocaa Network Technology Co Ltd
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Shenzhen Coocaa Network Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
    • H04N21/251—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
    • H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
    • H04N21/25866—Management of end-user data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/4508—Management of client data or end-user data
    • H04N21/4532—Management of client data or end-user data involving end-user characteristics, e.g. viewer profile, preferences
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Computer Graphics (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The invention discloses a program resource recommending method, which comprises the following steps: when the user attribute of a target user is obtained, judging whether a target resource set of the target user exists in a resource library or not by utilizing the user attribute; if the target resource set exists in the resource library, judging whether the target resource set meets a rejection condition or not by utilizing a first weight of the target resource set; if the target resource set meets the rejection condition, determining a recommended resource set which does not meet the rejection condition from the resource library by utilizing the user attribute, wherein the recommended resource set comprises first recommended resources; and performing program recommendation operation by using the first recommendation resource. The invention also discloses a recommendation device of the program resource, a program management engine and a storage medium. By using the method of the invention, the recommended resource set which does not meet the rejection condition is determined according to the user attribute of the target user, and the recommended resource set can be well matched with the requirements of the user.

Description

Program resource recommendation method and device, program management engine and storage medium
Technical Field
The present invention relates to the field of resource integration technologies, and in particular, to a method and an apparatus for recommending program resources, a program management engine, and a storage medium.
Background
At present, intelligent televisions are basically popular, various layouts or plates are arranged in the existing intelligent televisions, so that users can conveniently view various resources on the televisions, and a plurality of recommendation positions exist in the layout plates, and the recommendation positions display recommended resources to the users.
However, with the existing resource recommendation method, it is difficult to recommend resources to meet the user demands.
Disclosure of Invention
The invention mainly aims to provide a program resource recommending method, a device, a program management engine and a storage medium, and aims to solve the technical problem that the recommended resources are difficult to meet the demands of users by adopting the existing resource recommending mode in the prior art.
In order to achieve the above object, the present invention provides a recommendation method for program resources, the method comprising the following steps:
when the user attribute of a target user is obtained, judging whether a target resource set of the target user exists in a resource library or not by utilizing the user attribute;
if the target resource set exists in the resource library, judging whether the target resource set meets a rejection condition or not by utilizing a first weight of the target resource set;
if the target resource set meets the rejection condition, determining a recommended resource set which does not meet the rejection condition from the resource library by utilizing the user attribute, wherein the recommended resource set comprises first recommended resources;
and performing program recommendation operation by using the first recommendation resource.
Optionally, the step of determining, in the repository, a recommended resource set that does not satisfy the discard condition by using the user attribute if the target resource set satisfies the discard condition includes:
if the target resource set meets the rejection condition, judging whether an associated resource set associated with the target resource set exists in the resource library;
if the associated resource sets do not exist in the resource library, obtaining second weights of each resource set according to the description information of each resource set in the resource library and the user attribute;
sorting the second weights to obtain ordered weights;
acquiring resource heat collection degree information of each resource set;
and determining a recommended resource set which does not meet the rejection condition from the resource library according to the screening condition, the plurality of resource heat collection degree information and the ordered weight.
Optionally, after the step of determining the recommended resource set that does not meet the discard condition in the resource library according to the filtering condition, the plurality of resource heat collection information and the ordered weight, the method further includes:
determining a secondary selection recommended resource set which does not meet the rejection condition in the resource library according to the screening condition, the plurality of resource heat collection degree information and the ordered weight;
and establishing an association relation between the secondary selection recommended resource set and the recommended resource set.
Optionally, after the step of determining whether the target resource set of the target user exists in the resource library by using the user attribute, the method further includes:
if the target resource set does not exist in the resource library, judging whether a default recommended resource set exists in the resource library;
if the default recommended resource set does not exist in the resource library, randomly selecting a random recommended resource set in the resource library, wherein the random recommended resource set comprises second recommended resources;
and performing program recommendation operation by using the second recommendation resource.
Optionally, the first resource includes a plurality of; the step of performing program recommendation operation by using the first recommendation resource includes:
randomly determining a first selected first resource among a plurality of said first resources; and performing program recommendation operation by using the first selected first resource; or alternatively, the first and second heat exchangers may be,
obtaining a plurality of third weights corresponding to the plurality of first resources by using the description information of the plurality of first resources and the user attribute; determining a second selected first resource among the plurality of first resources according to the plurality of third weights; and performing program recommendation operation by using the second selected first resource.
Optionally, the target resource set includes a plurality of target resources; when the plurality of target resources are sequentially connected according to a preset sequence, before the step of judging whether the target resource set meets the rejection condition by using the first weight of the target resource set, the method further comprises:
determining a history resource which is recommended last time from a plurality of target resources, wherein the plurality of target resources are recommended according to the preset sequence;
judging whether the historical resource is the target resource at the tail end of the preset sequence or not;
the step of judging whether the target resource set meets the rejection condition by using the first weight of the target resource set comprises the following steps:
if the historical resource is the target resource at the tail end of the preset sequence, judging whether the target resource set meets the rejection condition or not by utilizing the first weight of the target resource set.
Optionally, the user attribute includes focus program information, member information, user city attribute information, and viewing record information of the target user.
In addition, in order to achieve the above object, the present invention further provides a recommendation device for program resources, where the device includes:
the acquisition module is used for judging whether a target resource set of the target user exists in the resource library or not by utilizing the user attribute when the user attribute of the target user is acquired;
the judging module is used for judging whether the target resource set meets a rejection condition or not by utilizing the first weight of the target resource set if the target resource set exists in the resource library;
the determining module is used for determining a recommended resource set which does not meet the rejection condition in the resource library by utilizing the user attribute if the target resource set meets the rejection condition, wherein the recommended resource set comprises first recommended resources;
and the recommending module is used for recommending the program by utilizing the first recommending resource.
In addition, to achieve the above object, the present invention also proposes a program management engine, including: the program recommendation system comprises a memory, a processor and a program recommendation program stored in the memory and running on the processor, wherein the program recommendation program is executed by the processor to realize the steps of the program recommendation method according to any one of the above.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon a program resource recommendation program which, when executed by a processor, implements the steps of the program resource recommendation method as set forth in any one of the above.
The invention provides a recommendation method of program resources, which comprises the following steps: when the user attribute of a target user is obtained, judging whether a target resource set of the target user exists in a resource library or not by utilizing the user attribute; if the target resource set exists in the resource library, judging whether the target resource set meets a rejection condition or not by utilizing a first weight of the target resource set; if the target resource set meets the rejection condition, determining a recommended resource set which does not meet the rejection condition from the resource library by utilizing the user attribute, wherein the recommended resource set comprises first recommended resources; and performing program recommendation operation by using the first recommendation resource.
In the existing resource recommendation mode, recommended resources are fixed and cannot be changed, so that recommended resources are single, and the requirements of users are difficult to meet. When the target resource set meets the rejection condition, the target resource set is not suitable for the requirement of the target user any more, and the recommended resource set which does not meet the rejection condition is determined according to the user attribute of the target user, so that the recommended resource set can be well matched with the requirement of the user, and the requirement of the user can be met by the recommended resource set.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical resource sets in the prior art, the drawings that are required in the embodiments or the prior art description will be briefly described, it being apparent that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a program management engine in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a first embodiment of a method for recommending program resources according to the present invention;
fig. 3 is a block diagram of a first embodiment of a recommendation device for program resources according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic diagram of a program management engine of a hardware running environment according to an embodiment of the present invention.
In general, a program management engine includes: at least one processor 301, a memory 302 and a recommendation program for program resources stored on said memory and executable on said processor, said recommendation program for program resources being configured to implement the steps of the recommendation method for program resources as described before.
Processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 301 may be implemented in at least one hardware form of DSP (Digital Signal Processing ), FPGA (Field-Programmable Gate Array, field programmable gate array), PLA (Programmable Logic Array ). The processor 301 may also include a main processor, which is a processor for processing data in an awake state, also called a CPU (Central ProcessingUnit ), and a coprocessor; a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 301 may integrate a GPU (Graphics Processing Unit, image processor) for rendering and drawing of content required to be displayed by the display screen. The processor 301 may also include an AI (Artificial Intelligence ) processor for processing recommended method operations for program resources such that a recommended method model for program resources may be trained and learned autonomously, improving efficiency and accuracy.
Memory 302 may include one or more storage media, which may be non-transitory. Memory 302 may also include high-speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory storage medium in memory 302 is used to store at least one instruction for execution by processor 301 to implement the recommendation method for program resources provided by the method embodiments herein.
In some embodiments, the terminal may further optionally include: a communication interface 303, and at least one peripheral device. The processor 301, the memory 302 and the communication interface 303 may be connected by a bus or signal lines. The respective peripheral devices may be connected to the communication interface 303 through a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 304, a display screen 305, and a power supply 306.
The communication interface 303 may be used to connect at least one peripheral device associated with an I/O (Input/Output) to the processor 301 and the memory 302. In some embodiments, processor 301, memory 302, and communication interface 303 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 301, the memory 302, and the communication interface 303 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.
The Radio Frequency circuit 304 is configured to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuitry 304 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 304 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 304 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuitry 304 may communicate with other terminals via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: metropolitan area networks, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (Wireless Fidelity ) networks. In some embodiments, the radio frequency circuitry 304 may also include NFC (Near Field Communication ) related circuitry, which is not limited in this application.
The display screen 305 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display 305 is a touch screen, the display 305 also has the ability to collect touch signals at or above the surface of the display 305. The touch signal may be input as a control signal to the processor 301 for processing. At this point, the display 305 may also be used to provide virtual buttons and/or virtual keyboards, also referred to as soft buttons and/or soft keyboards. In some embodiments, the display 305 may be one, the front panel of an electronic device; in other embodiments, the display screen 305 may be at least two, respectively disposed on different surfaces of the electronic device or in a folded design; in still other embodiments, the display 305 may be a flexible display disposed on a curved surface or a folded surface of the electronic device. Even more, the display screen 305 may be arranged in an irregular pattern other than rectangular, i.e., a shaped screen. The display 305 may be made of LCD (LiquidCrystal Display ), OLED (Organic Light-Emitting Diode) or other materials.
The power supply 306 is used to power the various components in the electronic device. The power source 306 may be alternating current, direct current, disposable or rechargeable. When the power source 306 comprises a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology. Those skilled in the art will appreciate that the architecture shown in fig. 1 is not limiting of the program management engine and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium stores a program resource recommending program, and the program resource recommending program realizes the steps of the program resource recommending method when being executed by a processor. Therefore, a detailed description will not be given here. In addition, the description of the beneficial effects of the same method is omitted. For technical details not disclosed in the embodiments of the storage medium related to the present application, please refer to the description of the method embodiments of the present application. As determined as an example, the program instructions may be deployed for execution on one program management engine, or on multiple program management engines located at one site, or on multiple program management engines distributed across multiple sites and interconnected by a communication network.
Those skilled in the art will appreciate that all or part of the above-described methods may be implemented by a computer program for instructing relevant hardware, and the above-described program may be stored in a storage medium, and the program may include the steps of the above-described embodiments of the methods when executed. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random access Memory (Random AccessMemory, RAM), or the like.
Based on the above hardware structure, an embodiment of the program resource recommendation method is provided.
Referring to fig. 2, fig. 2 is a flowchart of a first embodiment of a recommendation method for program resources according to the present invention, wherein the method is used for a program management engine, and the method includes the following steps:
step S11: when the user attribute of the target user is obtained, judging whether a target resource set of the target user exists in a resource library or not by utilizing the user attribute.
The execution subject of the present invention is a program management engine, the program management engine is provided with a program resource recommendation program, and when the program management engine executes the program resource recommendation program, the program resource recommendation method of the present invention is implemented. In some embodiments, the executing entity may also be a television set, which is connected to the internet, through which user attributes and various resources of the target user are obtained.
The target user is a user using a television, and the television sends user attribute information of the target user to the program management engine, and the user attribute of the target user may include focus program information (program information liked by the target user, such as a movie, a television show, or a game), member information (whether the target user is a paid member), user city attribute information (whether the target user is a city user), viewing record information (a program and a viewing time period watched by the target user), and the like.
The resource library refers to a preset resource library (or called a scheme group) in the program management engine, and the resource library includes a plurality of resource sets (or called schemes), each of which is a preset resource set, and each of which may include a plurality of resources (the resources refer to program resources, such as games, movies, music, or dramas, etc.).
Wherein, a resource set in the resource library may refer to a program category, and the granularity of the resource library is relatively large, such as an animation film (a resource library); the resources in the resource set refer to specific refinement types of the same program (the resources conforming to the same user attribute or the resources of the same category are the same program), the granularity in the resource set is small, and accurate recommendation can be performed, for example, scientific animation (one resource set). A resource refers to all the content that is operational, for example: television, movies, advertisements, games, etc., such as which specific piece of science fiction animation.
When the target user does not use the program management engine for the first time, the program management engine generally has a target resource set of the target user, the user attribute of the target user is obtained by the program management engine in the previous use process of the target user, and the program management engine determines a resource set in a resource library in the program management engine by utilizing the user attribute information, wherein the resource set is the target resource set.
When a target user uses a program management engine for the first time, the program management engine generally does not have a target resource set of the target user, and at the moment, if the target resource set does not exist in the resource library, judging whether a default recommended resource set exists in the resource library; if the default recommended resource set does not exist in the resource library, randomly selecting a random recommended resource set in the resource library, wherein the random recommended resource set comprises second recommended resources; and performing program recommendation operation by using the second recommendation resource. If the default recommended resource set exists in the resource library, program recommendation operation is performed by using third recommended resources included in the default resource set.
In the present invention, the program recommending operation may mean that a plurality of resources are included in a resource set, if the plurality of resources are sequentially connected according to a preset sequence (the sequence set by the user based on the requirement may be various types), a resource chain is formed, the resources in the resource chain arranged at the first position in the preset sequence are used as the resources recommended for the first time, the resources in the resource chain arranged at the second position in the preset sequence are used as the resources recommended for the second time, and so on, and then the recommended resources are sent to the television, and the recommended resources are displayed on the recommended layout by the television. The program recommending operation may be that when a plurality of resources are independent of each other, one resource is randomly selected in the resource set to recommend, the resource is sent to the television, and the recommended resource is displayed on a recommendation layout by the television. For example, a resource set includes 10 resources, 10 resources are linked together in a chain of resources, and 10 nodes are present.
The program recommending operation may also be that, when a plurality of resources are independent of each other, the description information and the user attribute of each resource in the resource set are utilized to determine the weight of each resource in the resource set, and the weight of each resource is utilized to determine the resource with the largest weight as the recommendation.
The recommended resources selected in the above three cases may be described as hit resources.
Different user attributes, when the description information of the resources is the same, the corresponding weights are different, for example, the user attribute information is children, the resource description information is a science fiction cartoon, and the weight of the science fiction cartoon is A; when the user attribute information is old people and the resource description information is the science fiction cartoon, the weight of the science fiction cartoon is B, and generally A is larger than B.
Step S12: if the target resource set exists in the resource library, judging whether the target resource set meets the rejection condition or not by utilizing the first weight of the target resource set.
When the target resource set exists in the resource library, whether the target resource set meets a rejection condition or not needs to be determined, wherein the rejection condition (outlet condition) means that the target resource set is not applicable to the target user any more, and when the first weight is generally lower than a preset weight threshold value, the target resource set is not applicable to the target user any more, and the target resource set meets the rejection condition; the first weight is determined by using three elements of the user attribute of the target user, the description information of the target resource set, and the retention time of the target resource set (the time the target user stays in the target resource set). It will be appreciated that the user attributes of the target user and the retention time of the target resource set may be updated in real time, and that the target resource set previously adapted to the target user may not be adapted to the target user any longer after the user attributes and retention time of the target user are updated.
Further, the set of target resources includes a plurality of target resources; when the plurality of target resources are sequentially connected according to a preset sequence, before the step of judging whether the target resource set meets the rejection condition by using the first weight of the target resource set, the method further comprises: determining a history resource which is recommended last time from a plurality of target resources, wherein the plurality of target resources are recommended according to the preset sequence; judging whether the historical resource is the target resource at the tail end of the preset sequence or not; the step of judging whether the target resource set meets the rejection condition by using the first weight of the target resource set comprises the following steps: if the historical resource is the target resource at the tail end of the preset sequence, judging whether the target resource set meets the rejection condition or not by utilizing the first weight of the target resource set.
The target resource set comprises a plurality of target resources, the target resources are sequentially connected according to a preset sequence to form a resource chain, the last recommended (hit) resource of the target resources is a history resource, the history resource is the last target resource of the resource chain, the target resource set reaches an outlet, and a first weight of the target resource set is needed to be utilized to judge whether the target resource set meets a rejection condition or not.
Meanwhile, if the history sub-resource is not the target resource at the end of the resource chain (the end of the preset sequence), determining the next target resource of the history sub-resource in the resource chain as a new recommended resource; and performing program recommendation operation by using the new recommended resources. That is, a plurality of the target resources are recommended in the preset order.
That is, if the history resource is not the last target resource of the resource chain, the target resource set reaches the unread outlet, the step of judging whether the target resource set meets the rejection condition or not is not needed to be performed by utilizing the first weight of the target resource set, and the next target resource of the history sub-resource in the resource chain is determined to be a new recommended resource; and performing program recommendation operation by utilizing the new recommended resources.
Step S13: and if the target resource set meets the rejection condition, determining a recommended resource set which does not meet the rejection condition from the resource library by utilizing the user attribute, wherein the recommended resource set comprises a first recommended resource.
Step S14: and performing program recommendation operation by using the first recommendation resource.
It should be noted that, with reference to the above description, when the target resource set satisfies the rejection condition, a new resource set of the target user, that is, a recommended resource set, needs to be determined, where the recommended resource set is used to replace the original target resource set of the target user, as the new target resource set.
Specifically, the step of determining, in the resource library, a recommended resource set that does not satisfy the discard condition by using the user attribute if the target resource set satisfies the discard condition includes: if the target resource set meets the rejection condition, judging whether an associated resource set associated with the target resource set exists in the resource library; if the associated resource sets do not exist in the resource library, obtaining second weights of each resource set according to the description information of each resource set in the resource library and the user attribute; sorting the second weights to obtain ordered weights; acquiring resource heat collection degree information of each resource set; and determining a recommended resource set which does not meet the rejection condition from the resource library according to the screening condition, the plurality of resource heat collection degree information and the ordered weight.
And when the associated resource set exists in the resource library, performing program recommendation operation by utilizing fourth resources included in the associated resource set.
Based on the above description, obtaining a weight-first weight-of each resource set in the resource library according to the description information of each resource set and the user attribute to obtain an ordered weight (the order is generally the order in which the weights are from high to low); meanwhile, heat information of each resource set, namely resource heat information, is also required to be collected, a part of resource sets with the first weight being greater than or equal to a preset weight threshold value is generally screened, then the heat information and the ordered weight are summarized and utilized in the part of resource sets, one resource set which is the best match is screened as a recommended resource set (the resource set with the highest heat is generally selected), the first weight of the recommended resource set is higher than the preset weight threshold value, and the recommended resource set does not meet the rejection condition.
The screening condition may be a user screening condition, a resource set meeting the screening condition is screened out from the resource library, and then a recommended resource set is determined according to a first weight of the resource set meeting the screening condition and resource heat collection information of the resource set meeting the screening condition.
Meanwhile, after the step of determining the recommended resource set which does not meet the rejection condition in the resource library according to the screening condition, the plurality of resource heat collection information and the ordered weight, the method further comprises the following steps: determining a secondary selection recommended resource set which does not meet the rejection condition in the resource library according to the screening condition, the plurality of resource heat collection degree information and the ordered weight; and establishing an association relation between the secondary selection recommended resource set and the recommended resource set.
The sub-selection recommended resource set is typically an option for which the resource heat collection information and the first weight are inferior to the recommended resource set. He is associated with a recommended resource set as an associated resource set of the recommended resource set, e.g. after the recommended resource set replaces the original target resource set of the target user, the original associated resource set of the target user is replaced by the sub-selected recommended resource set.
Further, the first resources comprise a plurality of first resources, and the plurality of first resources are mutually independent; the step of performing program recommendation operation by using the first recommendation resource includes:
randomly determining a first selected first resource among a plurality of said first resources; and performing program recommendation operation by using the first selected first resource; or alternatively, the first and second heat exchangers may be,
obtaining a plurality of third weights corresponding to the plurality of first resources by using the description information of the plurality of first resources and the user attribute; determining a second selected first resource among the plurality of first resources according to the plurality of third weights; and performing program recommendation operation by using the second selected first resource.
And recommending the first resources according to the mode when the first resources are independent of each other, and recommending one first resource in the first position of the preset sequence in the resource chain if the first resources are connected according to the preset sequence to form the resource chain.
The invention provides a recommendation method of program resources, which comprises the following steps: when the user attribute of a target user is obtained, judging whether a target resource set of the target user exists in a resource library or not by utilizing the user attribute; if the target resource set exists in the resource library, judging whether the target resource set meets a rejection condition or not by utilizing a first weight of the target resource set; if the target resource set meets the rejection condition, determining a recommended resource set which does not meet the rejection condition from the resource library by utilizing the user attribute, wherein the recommended resource set comprises first recommended resources; and performing program recommendation operation by using the first recommendation resource.
In the existing resource recommendation mode, recommended resources are fixed and cannot be changed, so that recommended resources are single, and the requirements of users are difficult to meet. When the target resource set meets the rejection condition, the target resource set is not suitable for the requirement of the target user any more, and the recommended resource set which does not meet the rejection condition is determined according to the user attribute of the target user, so that the recommended resource set can be well matched with the requirement of the user, and the requirement of the user can be met by the recommended resource set.
Referring to fig. 3, fig. 3 is a block diagram showing a first embodiment of a recommending apparatus for program resources according to the present invention, the apparatus being for a program management engine, the apparatus comprising, based on the same inventive concept as the previous embodiment:
the acquisition module 10 is configured to determine whether a target resource set of a target user exists in a resource library by using a user attribute when the user attribute of the target user is acquired;
a judging module 20, configured to, if the target resource set exists in the resource library, judge whether the target resource set meets a rejection condition by using a first weight of the target resource set;
a determining module 30, configured to determine, in the resource library, a recommended resource set that does not satisfy the rejection condition, using the user attribute, if the target resource set satisfies the rejection condition, where the recommended resource set includes a first recommended resource;
and a recommending module 40, configured to utilize the first recommending resource to perform a program recommending operation.
It should be noted that, since the steps executed by the apparatus of this embodiment are the same as those of the foregoing method embodiment, specific implementation manners and technical effects that can be achieved of the apparatus of this embodiment may refer to the foregoing embodiment, and will not be repeated herein.
The foregoing description is only of the optional embodiments of the present invention, and is not intended to limit the scope of the invention, and all the equivalent structural changes made by the description of the present invention and the accompanying drawings or the direct/indirect application in other related technical fields are included in the scope of the invention.

Claims (10)

1. A method for recommending program resources, the method comprising the steps of:
when the user attribute of a target user is obtained, judging whether a target resource set of the target user exists in a resource library or not by utilizing the user attribute;
if the target resource set exists in the resource library, judging whether the target resource set meets a rejection condition or not by utilizing a first weight of the target resource set;
if the target resource set meets the rejection condition, determining a recommended resource set which does not meet the rejection condition from the resource library by utilizing the user attribute, wherein the recommended resource set comprises first recommended resources;
and performing program recommendation operation by using the first recommendation resource.
2. The method of claim 1, wherein the step of determining a recommended set of resources in the repository that do not satisfy the discard condition using the user attribute if the target set of resources satisfies the discard condition comprises:
if the target resource set meets the rejection condition, judging whether an associated resource set associated with the target resource set exists in the resource library;
if the associated resource sets do not exist in the resource library, obtaining second weights of each resource set according to the description information of each resource set in the resource library and the user attribute;
sorting the second weights to obtain ordered weights;
acquiring resource heat collection degree information of each resource set;
and determining a recommended resource set which does not meet the rejection condition from the resource library according to the screening condition, the plurality of resource heat collection degree information and the ordered weight.
3. The method of claim 2, wherein after the step of determining a recommended set of resources in the repository that do not satisfy the discard condition based on the filtering condition, the plurality of resource heat collection information, and the ordered weight, the method further comprises:
determining a secondary selection recommended resource set which does not meet the rejection condition in the resource library according to the screening condition, the plurality of resource heat collection degree information and the ordered weight;
and establishing an association relation between the secondary selection recommended resource set and the recommended resource set.
4. The method of claim 1, wherein after the step of determining whether a target set of resources for the target user exists in a repository using the user attributes, the method further comprises:
if the target resource set does not exist in the resource library, judging whether a default recommended resource set exists in the resource library;
if the default recommended resource set does not exist in the resource library, randomly selecting a random recommended resource set in the resource library, wherein the random recommended resource set comprises second recommended resources;
and performing program recommendation operation by using the second recommendation resource.
5. The method of claim 1, wherein the first resource comprises a plurality of the first resources independent of each other; the step of performing program recommendation operation by using the first recommendation resource includes:
randomly determining a first selected first resource among a plurality of said first resources; and performing program recommendation operation by using the first selected first resource; or alternatively, the first and second heat exchangers may be,
obtaining a plurality of third weights corresponding to the plurality of first resources by using the description information of the plurality of first resources and the user attribute; determining a second selected first resource among the plurality of first resources according to the plurality of third weights; and performing program recommendation operation by using the second selected first resource.
6. The method of claim 1, wherein the set of target resources comprises a plurality of target resources; when the plurality of target resources are sequentially connected according to a preset sequence, before the step of judging whether the target resource set meets the rejection condition by using the first weight of the target resource set, the method further comprises:
determining a history resource which is recommended last time from a plurality of target resources, wherein the plurality of target resources are recommended according to the preset sequence;
judging whether the historical resource is the target resource at the tail end of the preset sequence or not;
the step of judging whether the target resource set meets the rejection condition by using the first weight of the target resource set comprises the following steps:
if the historical resource is the target resource at the tail end of the preset sequence, judging whether the target resource set meets the rejection condition or not by utilizing the first weight of the target resource set.
7. The method of any one of claims 1-6, wherein the user attributes include focus program information, member information, user metropolitan attribute information, and viewing record information of the target user.
8. A recommendation device for program resources, the device comprising:
the acquisition module is used for judging whether a target resource set of the target user exists in the resource library or not by utilizing the user attribute when the user attribute of the target user is acquired;
the judging module is used for judging whether the target resource set meets a rejection condition or not by utilizing the first weight of the target resource set if the target resource set exists in the resource library;
the determining module is used for determining a recommended resource set which does not meet the rejection condition in the resource library by utilizing the user attribute if the target resource set meets the rejection condition, wherein the recommended resource set comprises first recommended resources;
and the recommending module is used for recommending the program by utilizing the first recommending resource.
9. A program management engine, the program management engine comprising: memory, a processor and a program stored on the memory and running on the processor a recommendation for a program resource, which when executed by the processor implements the steps of the program resource recommendation method according to any one of claims 1 to 7.
10. A storage medium, wherein a program resource recommendation program is stored on the storage medium, and wherein the program resource recommendation program, when executed by a processor, implements the steps of the program resource recommendation method according to any one of claims 1 to 7.
CN202111479456.7A 2021-12-06 2021-12-06 Program resource recommendation method and device, program management engine and storage medium Pending CN116233495A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117648471A (en) * 2024-01-30 2024-03-05 深圳鹏锐信息技术股份有限公司 Three-dimensional industrial design material AI intelligent recommendation management system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117648471A (en) * 2024-01-30 2024-03-05 深圳鹏锐信息技术股份有限公司 Three-dimensional industrial design material AI intelligent recommendation management system
CN117648471B (en) * 2024-01-30 2024-04-09 深圳鹏锐信息技术股份有限公司 Three-dimensional industrial design material AI intelligent recommendation management system

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