CN113282853A - Comment preloading method and device, storage medium and electronic equipment - Google Patents
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Abstract
The embodiment of the invention discloses a comment preloading method, a comment preloading device, a storage medium and electronic equipment, wherein the method comprises the following steps: acquiring object characteristics of a current display object and user characteristics corresponding to equipment for displaying the current display object; predicting the object characteristics and the user characteristics based on a comment prediction model, and determining the comment preloading probability of the current display object; and if the comment preloading probability meets the preloading condition, preloading the comment of the current display object. The comments with the preloading requirements are preloaded, so that resource waste caused by loading of invalid comments is avoided, and the accuracy and the recall rate of the preloaded comments are improved. Meanwhile, the pre-loading of the comments is to record the comments in advance and cache the comments locally when the user does not click the comments, so that the pre-loaded comments can be called locally to be displayed when the user clicks the comments, and the waiting time from the comment clicking to the comment displaying is shortened.
Description
Technical Field
The embodiment of the invention relates to the technical field of computer data processing, in particular to a comment preloading method and device, a storage medium and electronic equipment.
Background
In the interactive scene of the short video, the user can click on the comment area or the comment button to display the user comment of the short video being played. The loading of the current comments can be obtained by requesting the server to download through a loading request generated by clicking operation of a user, and waiting caused by a request process exists; the comment can be loaded by preloading when the short video is clicked and played, but when the user does not click the comment to switch the short video, the preloaded comment is invalid and consumes a large amount of server resources.
Disclosure of Invention
The embodiment of the invention provides a comment preloading method and device, a storage medium and electronic equipment, so as to realize accurate preloading of comments.
In a first aspect, an embodiment of the present invention provides a comment preloading method, including:
acquiring object characteristics of a current display object and user characteristics corresponding to equipment for displaying the current display object;
predicting the object characteristics and the user characteristics based on a comment prediction model, and determining the comment preloading probability of the current display object;
and if the comment preloading probability meets the preloading condition, preloading the comment of the current display object.
In a second aspect, an embodiment of the present invention further provides a comment preloading device, including:
the characteristic acquisition module is used for acquiring the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object;
the probability prediction module is used for performing prediction processing on the object characteristics and the user characteristics based on a comment prediction model and determining the comment preloading probability of the current display object;
and the comment preloading module is used for preloading the comment of the current display object if the comment preloading probability meets the preloading condition.
In a third aspect, an embodiment of the present disclosure further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a comment preloading method as described in any one of the embodiments of the present disclosure.
In a fourth aspect, the disclosed embodiments also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are used to perform the comment preloading method as described in any one of the disclosed embodiments.
According to the technical scheme, in the display process of the current display object, the object characteristics and the user characteristics of the current display object are predicted and processed based on the comment prediction model, the comment preloading probability of the current display object is determined, and the comments of the current display object are preloaded when the comment preloading probability meets the preloading condition so as to preload the comments with preloading requirements, so that resource waste caused by loading of invalid comments is avoided, and the accuracy and the recall rate of the preloaded comments are improved. Meanwhile, the pre-loading of the comments is to record the comments in advance and cache the comments locally when the user does not click the comments, so that the pre-loaded comments can be called locally to be displayed when the user clicks the comments, and the waiting time from the comment clicking to the comment displaying is shortened.
Drawings
Fig. 1 is a flowchart of a comment preloading method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a comment prediction model provided by an embodiment of the present invention;
FIG. 3 is a flow diagram of comment preloading prediction provided by an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a comment preloading device according to a second embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
Example one
Fig. 1 is a flowchart of a comment preloading method provided in an embodiment of the present invention, where this embodiment is applicable to a case of predicting comment preloading, and the method may be executed by a comment preloading device provided in an embodiment of the present invention, where the comment preloading device may be implemented by software and/or hardware, and the comment preloading device may be configured on an electronic computing device, and specifically includes the following steps:
s110, obtaining object characteristics of the current display object and user characteristics corresponding to equipment for displaying the current display object.
S120, predicting the object characteristics and the user characteristics based on a comment prediction model, and determining the comment preloading probability of the current display object.
S130, if the comment preloading probability meets the preloading condition, preloading the comment of the current display object.
In this embodiment, the display object may be displayed based on an electronic device, and the electronic device may be a terminal device configured with a display interface, such as a mobile phone, a tablet computer, a PC terminal, and the like. And displaying the display object and the comment of the display object through the display interface. The current exhibition objects include, but are not limited to, videos (including short videos, normal videos, and the like), documents (e.g., news, papers, periodicals, and the like), pictures, and the like. Particularly, for short videos, the comment loading duration is increased aiming at the characteristics of short video playing time, high switching frequency and the like, the short video browsing process of a user is affected, meanwhile, the short video switching speed is high, the number of short videos to be displayed is large, a large amount of loading resources are consumed due to the fact that each short video is subjected to comment preloading, and the recall rate is low.
In order to solve the above problem, in this embodiment, a set comment prediction model is used to perform comment preloading prediction on a current display object to obtain a probability that a user needs a comment of the current display object, and the comment is preloaded in a targeted manner based on the probability value, where the comment is preloaded by recording the comment in advance and caching the comment locally when the user does not click the comment, so that when the user clicks the comment, the preloaded comment can be called locally for display, and the waiting time from the comment click to the comment display is reduced. Meanwhile, whether comment preloading is carried out is determined according to the probability predicted by the comment prediction model so as to preload the comments with preloading requirements, resource waste caused by loading of invalid comments is avoided, and the accuracy and the recall rate of the preloaded comments are improved.
In this embodiment, the object characteristics of the current display object and the user characteristics of the device are subjected to prediction processing based on the comment prediction model, so as to obtain the comment preloading probability of the current display object. The object features and the user features are provided by user authorization, and specifically, for any user, in the process of displaying any object by user equipment, the operations of the user on the displayed object are acquired, wherein the operations include but are not limited to comment clicking, praise, sharing, setting to like, and completely displaying the displayed object. Specifically, the number of times of corresponding operations of any acquired operation on the user characteristics may be increased by one locally on the device, or the data may be uploaded to the server, so that the server increases the number of times of corresponding operations on the display object based on the operations on the display object by one, and the object characteristics of the display object may be obtained by counting the sum of the number of times of operations on the display object by different users. It should be noted that the user characteristic may be data within a preset time period, and the preset time period may be a preset time period before the current time, for example, a week or a month before the current time, which is not limited in this regard. The data acquired by the device may include a timestamp of any operation, and according to the timestamp of each operation, the operation data that is not in the preset time period is deleted, for example, if the sharing operation of the video a is not in the preset time period, the number of sharing times in the user characteristics is reduced by one. Optionally, different user characteristics may be set according to the type of the display object for different types of the display object, such as short video, normal video, news, pictures, and the like, so as to facilitate high-precision prediction for each type of the display object.
When any display object is in a display state, the user characteristics may be read locally from the device, and the object characteristics of the display object may be obtained from the server. The object characteristics include operation characteristic information of the different devices on the current display object, and in some optional embodiments, the object characteristics include one or more of display times, complete display times, comment times, like times and sharing times of the current display object. The display times in the object characteristics can be the sum of the display times of the current display object on different equipment, and the display times can be added by one when the current display object is displayed on a display interface; the complete display times may be the sum of the complete display times of the current display object on different devices, the complete display may be that all contents of the current display object are displayed on the display interface, or that core contents of the current display object (for example, contents except for a title and a trailer in video contents) are displayed on the display interface, that is, the complete display times are counted plus one, and the comment times, the approval times and the sharing times are respectively the sum of the times that the current display object is commented on, approved and shared on different devices.
The user characteristics comprise operation characteristic information of each display object of the object type of the current display object in preset time. In some optional embodiments, the user characteristics include one or more of the number of presentations, the number of complete presentations, the number of clicks on comments, the number of praise and the number of shares of the object type to which the current presentation object belongs within a preset time. The object type may be determined according to a format of the current display object, for example, if the current display object is a short video, the display times are display times of each short video within a preset time. In some alternative embodiments, the object type may also be a domain determination of the currently presented object, for example, the object type may include, but is not limited to, military, entertainment, academic, diploma, travel, electronic devices, apparel, and the like. The display times in the user characteristics are the sum of the display times of all display objects in the object type to which the current display object belongs within the preset time of the current equipment, the complete display times are the sum of the complete display times of all display objects in the object type to which the current display object belongs within the preset time of the current equipment, and the comment times, the like-pointing times and the sharing times are the sum of the times that all display objects in the object type to which the current display object belongs are commented, liked and shared respectively within the preset time of the current equipment.
And predicting the object characteristics and the user characteristics based on the comment prediction model, fusing the characteristics of different dimensions, and improving the prediction accuracy of the comment prediction model. The comment prediction model can be a decision tree model or a neural network model, is not limited, and can realize a comment preloading prediction function.
On the basis of the above embodiment, the comment prediction model includes a feature extraction module, a feature conversion module, and a probability prediction module. In some optional embodiments, the feature extraction module includes a Tree structure-feature extraction module, for example, a GBDT (Gradient Boosting Decision Tree) Tree structure-feature extraction module, the feature transformation module is a one-hot structure, and the probability prediction module is an LR (logical Regression) structure, for example, see fig. 2, where fig. 2 is a schematic structural diagram of a comment prediction model provided in the embodiment of the present invention. It should be noted that the comment prediction model in fig. 2 is only a schematic diagram, and the specific structure thereof is not limited, and the specific structure and parameters of each module in the comment prediction model can be adjusted according to the needs.
Correspondingly, the step of performing prediction processing on the object characteristics and the user characteristics based on a comment prediction model to determine the comment preloading probability of the currently displayed object includes: performing feature extraction on the object features and the user features based on the feature extraction module; performing feature conversion on the extracted feature information based on the feature conversion module; and carrying out probability prediction on the feature information obtained by conversion based on the probability prediction module to obtain the comment preloading probability of the current display object.
In this embodiment, the object features and the user features are converted into input information adapted to the comment prediction model, and the input information may be in a vector format. The input information in the vector format is input to a feature extraction module of the comment prediction model to obtain feature information corresponding to the input information, and a feature conversion module converts the feature information into conversion features adapted to the probability prediction module, for example, the conversion features may be feature information in a one-hot vector format. The conversion characteristics are input into a probability prediction module to obtain the comment preloading probability of the current display object, and the comment preloading prediction of the display object is achieved.
Specifically, if the comment preloading probability exceeds the probability threshold, the comment preloading of the current display object is performed, and if the comment preloading probability does not exceed the probability threshold, the comment preloading of the current display object is not performed, so that resource waste caused by invalid preloading is avoided. In some alternative embodiments, the probability threshold may be 70%.
It should be noted that the probability prediction module may be obtained by training based on offline sample data, where the sample data includes user features and object features of each display object, and a tag is a comment click tag of a user on a display object, and for example, if a user clicks a comment on a display object, the tag is 1, and if a user does not click a comment on a display object, the tag is 0. And performing iterative training based on the offline sample data and the corresponding label until the training times are met or the convergence state is reached, and obtaining a trained comment prediction model.
On the basis of the above embodiment, before obtaining the object feature of the current display object and the user feature corresponding to the device for displaying the current display object, the method further includes: and acquiring the display duration of the current display object, and executing the steps of acquiring the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object when the display duration meets the preset duration. By obtaining the display duration of the current display object, when the display duration of the current display object is greater than or equal to the preset duration, the prediction of comment preloading is carried out on the current display object, when the display duration of the current display object is smaller than the preset duration, and the display object is switched through switching operations such as sliding operation and the like, the prediction of comment preloading is not carried out, invalid comment preloading prediction caused by rapid switching of the current display object is avoided, and the pertinence of the prediction of comment preloading is provided. Illustratively, referring to fig. 3, fig. 3 is a schematic flow chart of comment preloading prediction provided by the embodiment of the present invention. In fig. 3, taking the current display object as the video as an example, in the display process of the current display object, it is determined whether the display duration is greater than or equal to the preset duration X, where the preset duration may be 5S, and if not, the display duration of the switched display object is obtained. If so, predicting comment preloading based on the offline-trained machine learning model, namely the comment prediction model, obtaining a comment preloading probability, determining whether the comment preloading probability is greater than or equal to a probability threshold value Y, if so, preloading the comment, and if not, not preloading the comment.
On the basis of the above embodiment, preloading the comment of the current presentation object includes: determining a pre-loaded comment amount based on the comment amount of the current display object and the displayable comment amount of a display page; and preloading comments based on the pre-loaded comment amount. In this embodiment, because the comment amounts of different display objects are different, in order to avoid the situation of preloading a large number of invalid comments, a preloaded comment amount is determined, and preloading is performed based on the preloaded comment amount. And the pre-loaded comment quantity is less than or equal to the displayable comment quantity of the display page, so that the accuracy and the recall rate of the pre-loaded comment are improved. For example, if the comment amount of the current display object is greater than the displayable comment amount of the display page, the displayable comment amount of the display page is determined as the preloaded comment amount, and if the comment amount of the current display object is less than or equal to the displayable comment amount of the display page, the comment amount of the current display object is determined as the preloaded comment amount.
In the display process of the preloaded comments, if the sliding operation or the updating operation of the comment content is obtained, other comment information of the current display object is loaded, for example, comment loading can be performed by taking the displayable comment amount of the display page as a loading unit, so that the situations of long waiting time and loading of invalid comments caused by all loading are avoided.
Specifically, the pre-loading of the comment may be to determine the content of the comment to be pre-loaded according to the comment timestamp and the comment value amount, so as to load the latest comment content.
According to the technical scheme, in the display process of the current display object, the object characteristics and the user characteristics of the current display object are predicted and processed based on the comment prediction model, the comment preloading probability of the current display object is determined, and the comments of the current display object are preloaded when the comment preloading probability meets the preloading condition so as to preload the comments with preloading requirements, so that resource waste caused by loading of invalid comments is avoided, and the accuracy and the recall rate of the preloaded comments are improved. Meanwhile, the pre-loading of the comments is to record the comments in advance and cache the comments locally when the user does not click the comments, so that the pre-loaded comments can be called locally to be displayed when the user clicks the comments, and the waiting time from the comment clicking to the comment displaying is shortened.
Example two
Fig. 4 is a schematic structural diagram of a comment preloading device according to a second embodiment of the present invention, where the comment preloading device includes a feature obtaining module 210, a probability predicting module 220, and a comment preloading module 230.
A feature obtaining module 210, configured to obtain an object feature of a current display object and a user feature corresponding to a device used for displaying the current display object;
a probability prediction module 220, configured to perform prediction processing on the object feature and the user feature based on a comment prediction model, and determine a comment preloading probability of the current display object;
230, configured to preload the comment of the current display object if the comment preloading probability meets a preloading condition.
According to the technical scheme, in the display process of the current display object, the object characteristics and the user characteristics of the current display object are predicted and processed based on the comment prediction model, the comment preloading probability of the current display object is determined, and the comments of the current display object are preloaded when the comment preloading probability meets the preloading condition so as to preload the comments with preloading requirements, so that resource waste caused by loading of invalid comments is avoided, and the accuracy and the recall rate of the preloaded comments are improved. Meanwhile, the pre-loading of the comments is to record the comments in advance and cache the comments locally when the user does not click the comments, so that the pre-loaded comments can be called locally to be displayed when the user clicks the comments, and the waiting time from the comment clicking to the comment displaying is shortened.
On the basis of the technical scheme, the object characteristics comprise one or more of the display times, the complete display times, the comment times, the like times and the sharing times of the current display object;
the user characteristics comprise one or more of display times, complete display times, comment click times, comment times, like times and sharing times of the object type to which the current display object belongs within preset time.
On the basis of the technical scheme, the device further comprises:
the display duration obtaining module is used for obtaining the display duration of the current display object before obtaining the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object, and executing the steps of obtaining the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object when the display duration meets the preset duration.
On the basis of the technical scheme, the current display object comprises a video.
On the basis of the technical scheme, the comment prediction model comprises a feature extraction module, a feature conversion module and a probability prediction module;
the probability prediction module 220 is configured to:
performing feature extraction on the object features and the user features based on the feature extraction module;
performing feature conversion on the extracted feature information based on the feature conversion module;
and carrying out probability prediction on the feature information obtained by conversion based on the probability prediction module to obtain the comment preloading probability of the current display object.
On the basis of the above technical solution, the comment preloading module 230 is configured to:
determining a pre-loaded comment amount based on the comment amount of the current display object and the displayable comment amount of a display page;
and preloading comments based on the pre-loaded comment amount.
On the basis of the technical scheme, the pre-loaded comment quantity is less than or equal to the displayable comment quantity of the display page.
The comment preloading device provided by the embodiment of the invention can execute the comment preloading method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the comment preloading method.
EXAMPLE III
Referring now to fig. 5, a schematic diagram of an electronic device (e.g., the terminal device or the server of fig. 5) 400 suitable for implementing embodiments of the present disclosure is shown. The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 400 may include a processing device (e.g., central processing unit, graphics processor, etc.) 401 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage device 408 into a Random Access Memory (RAM) 403. In the RAM403, various programs and data necessary for the operation of the electronic apparatus 400 are also stored. The processing device 401, the ROM402, and the RAM403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
Generally, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the electronic device 400 to communicate wirelessly or by wire with other devices to exchange data. While fig. 5 illustrates an electronic device 400 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication device 409, or from the storage device 408, or from the ROM 402. The computer program performs the above-described functions defined in the methods of the embodiments of the present disclosure when executed by the processing device 401.
The electronic device provided by the embodiment of the disclosure and the comment preloading method provided by the above embodiment belong to the same inventive concept, and technical details that are not described in detail in the embodiment can be referred to the above embodiment, and the embodiment has the same beneficial effects as the above embodiment.
EXAMPLE five
The disclosed embodiments provide a computer storage medium on which a computer program is stored, which when executed by a processor implements the comment preloading method provided by the above-described embodiments.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to:
acquiring object characteristics of a current display object and user characteristics corresponding to equipment for displaying the current display object;
predicting the object characteristics and the user characteristics based on a comment prediction model, and determining the comment preloading probability of the current display object;
and if the comment preloading probability meets the preloading condition, preloading the comment of the current display object.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a unit/module does not in some cases constitute a limitation of the unit itself.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
According to one or more embodiments of the present disclosure, [ example one ] there is provided a comment preloading method, including:
acquiring object characteristics of a current display object and user characteristics corresponding to equipment for displaying the current display object;
predicting the object characteristics and the user characteristics based on a comment prediction model, and determining the comment preloading probability of the current display object;
and if the comment preloading probability meets the preloading condition, preloading the comment of the current display object.
According to one or more embodiments of the present disclosure, [ example two ] there is provided a comment preloading method, further comprising:
the object characteristics comprise operation characteristic information of the different devices on the current display object;
the user characteristics comprise operation characteristic information of each display object of the object type of the current display object in preset time.
According to one or more embodiments of the present disclosure, [ example three ] there is provided a comment preloading method, further comprising:
optionally, before obtaining the object feature of the current display object and the user feature corresponding to the device for displaying the current display object, the method further includes:
and acquiring the display duration of the current display object, and executing the steps of acquiring the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object when the display duration meets the preset duration.
According to one or more embodiments of the present disclosure, [ example four ] there is provided a comment preloading method, further comprising:
optionally, the current display object includes a video.
According to one or more embodiments of the present disclosure, [ example five ] there is provided a comment preloading method, further comprising:
optionally, the comment prediction model includes a feature extraction module, a feature conversion module, and a probability prediction module;
the predicting the object characteristics and the user characteristics based on the comment prediction model to determine the comment preloading probability of the current display object comprises the following steps:
performing feature extraction on the object features and the user features based on the feature extraction module;
performing feature conversion on the extracted feature information based on the feature conversion module;
and carrying out probability prediction on the feature information obtained by conversion based on the probability prediction module to obtain the comment preloading probability of the current display object.
According to one or more embodiments of the present disclosure, [ example six ] there is provided a comment preloading method, further comprising:
optionally, the preloading the comment of the current display object includes:
determining a pre-loaded comment amount based on the comment amount of the current display object and the displayable comment amount of a display page;
and preloading comments based on the pre-loaded comment amount.
According to one or more embodiments of the present disclosure, [ example seven ] there is provided a comment preloading method, further comprising:
optionally, the pre-loaded comment amount is less than or equal to the displayable comment amount of the display page.
According to one or more embodiments of the present disclosure, [ example eight ] there is provided a comment preloading device including:
the characteristic acquisition module is used for acquiring the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object;
the probability prediction module is used for performing prediction processing on the object characteristics and the user characteristics based on a comment prediction model and determining the comment preloading probability of the current display object;
and the comment preloading module is used for preloading the comment of the current display object if the comment preloading probability meets the preloading condition.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (10)
1. A comment preloading method is characterized by comprising the following steps:
acquiring object characteristics of a current display object and user characteristics corresponding to equipment for displaying the current display object;
predicting the object characteristics and the user characteristics based on a comment prediction model, and determining the comment preloading probability of the current display object;
and if the comment preloading probability meets the preloading condition, preloading the comment of the current display object.
2. The method according to claim 1, wherein the object characteristics comprise operation characteristic information of different devices on the currently displayed object;
the user characteristics comprise operation characteristic information of each display object of the object type of the current display object in preset time.
3. The method according to claim 1, wherein before obtaining the object feature of the current display object and the user feature corresponding to the device for displaying the current display object, the method further comprises:
and acquiring the display duration of the current display object, and executing the steps of acquiring the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object when the display duration meets the preset duration.
4. A method according to any of claims 1-3, wherein the currently presented object comprises a video.
5. The method of claim 1, wherein the opinion prediction model comprises a feature extraction module, a feature transformation module, and a probability prediction module;
the predicting the object characteristics and the user characteristics based on the comment prediction model to determine the comment preloading probability of the current display object comprises the following steps:
performing feature extraction on the object features and the user features based on the feature extraction module;
performing feature conversion on the extracted feature information based on the feature conversion module;
and carrying out probability prediction on the feature information obtained by conversion based on the probability prediction module to obtain the comment preloading probability of the current display object.
6. The method of claim 1, wherein preloading the comments of the currently presented object comprises:
determining a pre-loaded comment amount based on the comment amount of the current display object and the displayable comment amount of a display page;
and preloading comments based on the pre-loaded comment amount.
7. The method of claim 6, wherein the pre-loaded argument is less than or equal to a displayable argument of the display page.
8. A review preloading device, comprising:
the characteristic acquisition module is used for acquiring the object characteristics of the current display object and the user characteristics corresponding to the equipment for displaying the current display object;
the probability prediction module is used for performing prediction processing on the object characteristics and the user characteristics based on a comment prediction model and determining the comment preloading probability of the current display object;
and the comment preloading module is used for preloading the comment of the current display object if the comment preloading probability meets the preloading condition.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the comment preloading method as recited in any one of claims 1-7.
10. A storage medium containing computer-executable instructions for performing the comment preloading method as recited in any one of claims 1-7 when executed by a computer processor.
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180129660A1 (en) * | 2016-11-10 | 2018-05-10 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method and apparatus for pushing information |
| CN108174278A (en) * | 2018-01-30 | 2018-06-15 | 河南职业技术学院 | Barrage display methods and barrage display device |
| CN108647052A (en) * | 2018-04-28 | 2018-10-12 | Oppo广东移动通信有限公司 | Application program preloads method, apparatus, storage medium and terminal |
| CN108804157A (en) * | 2018-06-05 | 2018-11-13 | Oppo广东移动通信有限公司 | Application program preloads method, apparatus, storage medium and terminal |
| CN108958828A (en) * | 2018-05-21 | 2018-12-07 | Oppo广东移动通信有限公司 | Application program preloads method, apparatus, storage medium and terminal |
| CN109492160A (en) * | 2018-10-31 | 2019-03-19 | 北京字节跳动网络技术有限公司 | Method and apparatus for pushed information |
| CN109688479A (en) * | 2018-12-26 | 2019-04-26 | 北京蓦然认知科技有限公司 | A kind of barrage display methods, barrage display device and barrage display server |
| CN109862432A (en) * | 2019-01-31 | 2019-06-07 | 厦门美图之家科技有限公司 | Clicking rate prediction technique and device |
| CN110298126A (en) * | 2019-07-04 | 2019-10-01 | 北京航空航天大学 | A kind of polynary Copula power device method for evaluating reliability based on the physics of failure |
| US20190370095A1 (en) * | 2018-05-29 | 2019-12-05 | Guangdong Oppo Mobile Telecommunications Corp., Ltd. | Method and device for preloading application, storage medium and intelligent terminal |
| CN111246275A (en) * | 2020-02-07 | 2020-06-05 | 北京字节跳动网络技术有限公司 | Comment information display and interaction method and device, electronic equipment and storage medium |
| CN111432246A (en) * | 2020-03-23 | 2020-07-17 | 广州市百果园信息技术有限公司 | Method, device and storage medium for pushing video data |
| CN112131410A (en) * | 2020-09-18 | 2020-12-25 | 北京达佳互联信息技术有限公司 | Multimedia resource display method, device, system and storage medium |
-
2021
- 2021-05-26 CN CN202110578552.0A patent/CN113282853B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180129660A1 (en) * | 2016-11-10 | 2018-05-10 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method and apparatus for pushing information |
| CN108174278A (en) * | 2018-01-30 | 2018-06-15 | 河南职业技术学院 | Barrage display methods and barrage display device |
| CN108647052A (en) * | 2018-04-28 | 2018-10-12 | Oppo广东移动通信有限公司 | Application program preloads method, apparatus, storage medium and terminal |
| CN108958828A (en) * | 2018-05-21 | 2018-12-07 | Oppo广东移动通信有限公司 | Application program preloads method, apparatus, storage medium and terminal |
| US20190370095A1 (en) * | 2018-05-29 | 2019-12-05 | Guangdong Oppo Mobile Telecommunications Corp., Ltd. | Method and device for preloading application, storage medium and intelligent terminal |
| CN108804157A (en) * | 2018-06-05 | 2018-11-13 | Oppo广东移动通信有限公司 | Application program preloads method, apparatus, storage medium and terminal |
| CN109492160A (en) * | 2018-10-31 | 2019-03-19 | 北京字节跳动网络技术有限公司 | Method and apparatus for pushed information |
| CN109688479A (en) * | 2018-12-26 | 2019-04-26 | 北京蓦然认知科技有限公司 | A kind of barrage display methods, barrage display device and barrage display server |
| CN109862432A (en) * | 2019-01-31 | 2019-06-07 | 厦门美图之家科技有限公司 | Clicking rate prediction technique and device |
| CN110298126A (en) * | 2019-07-04 | 2019-10-01 | 北京航空航天大学 | A kind of polynary Copula power device method for evaluating reliability based on the physics of failure |
| CN111246275A (en) * | 2020-02-07 | 2020-06-05 | 北京字节跳动网络技术有限公司 | Comment information display and interaction method and device, electronic equipment and storage medium |
| CN111432246A (en) * | 2020-03-23 | 2020-07-17 | 广州市百果园信息技术有限公司 | Method, device and storage medium for pushing video data |
| CN112131410A (en) * | 2020-09-18 | 2020-12-25 | 北京达佳互联信息技术有限公司 | Multimedia resource display method, device, system and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| MING CHUN LEE等: "Individual preference probability modeling for video content in wireless caching networks", 《GLOBECOM 2017 -2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE》, 15 January 2018 (2018-01-15), pages 1 - 4 * |
| 贾金原 等: "基于DR预测的大规模Web3D场景预加载机制", 《系统仿真学报》, vol. 32, no. 7, 30 March 2020 (2020-03-30), pages 1341 - 1348 * |
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