CN114357305A - Live broadcast object explanation sequence determination method and device of real-time live broadcast room - Google Patents
Live broadcast object explanation sequence determination method and device of real-time live broadcast room Download PDFInfo
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Abstract
The embodiment of the application provides a live broadcast object explanation sequence determination method and device of a real-time live broadcast room, wherein the live broadcast object explanation sequence determination method of the real-time live broadcast room comprises the following steps: acquiring interactive behavior data of current online audiences in a live broadcast room; analyzing the interactive behavior data to obtain preference attribute information of the online audience; the preference attribute information is live broadcast object attribute information which has a strong association relation with the interactive behavior participated by the online audience; acquiring self attribute information of a live object to be explained in a live broadcast room, wherein the self attribute information represents the live object attribute information of the live object to be explained; and determining the explanation sequence of the live objects to be explained based on the matching degree between the preference attribute information and the attribute information of the live objects to be explained. According to the embodiment of the application, the live broadcasting object of the current explanation can be better matched with the preference of the online audience, the possibility that the online audience purchases commodities is increased, and the live broadcasting effect is improved.
Description
Technical Field
The embodiment of the application relates to the technical field of internet, in particular to a live broadcast object explanation sequence determining method, device and equipment for a real-time live broadcast room and a computer storage medium.
Background
With the rise of live broadcast platforms, people's daily life has also changed greatly, and more live broadcast users recommend and sell commodities through the electronic live broadcast platform.
A live broadcast typically involves a plurality of different commodities, and it has an important influence on the performance of live broadcast sales that during the live broadcast, which commodity is spoken first and then which commodity is spoken later. At present, before broadcasting, the explanation sequence of each commodity is preset mainly by a main broadcaster or a professional according to own experience, and after broadcasting, the explanation is sequentially carried out according to the fixed sequence.
The above manner is mainly completed by manual experience, and the commodity explanation sequence is not changed once being determined, so that the commodity explanation is performed according to the order determined by the manner, and the purchase demand of the watching user with dynamic change may not be well met, thereby resulting in poor live broadcast effect.
Disclosure of Invention
In view of the above, an embodiment of the present invention provides a live object interpretation order determination method in a real-time live broadcast room, so as to at least partially solve the above problem.
According to a first aspect of the embodiments of the present application, there is provided an explanation order determination method, including:
acquiring interactive behavior data of current online audiences in a live broadcast room; the interactive behavior data characterizes interactive behaviors that the online audience has participated in;
analyzing the interaction behavior data to obtain preference attribute information of online audiences; the preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior participated by the online audience;
acquiring self attribute information of a live object to be explained in the live broadcast room, wherein the self attribute information represents the live object attribute information of the live object to be explained;
and determining the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the attribute information of the live object to be explained.
According to a second aspect of the embodiments of the present application, there is provided a live object explanation order determination apparatus in a real-time live broadcast room, including:
the interactive behavior data acquisition module is used for acquiring the interactive behavior data of the current online audience in the live broadcast room; the interactive behavior data characterizes interactive behaviors that the online audience has participated in;
the preference attribute information obtaining module is used for analyzing the interaction behavior data to obtain preference attribute information of the online audience; the preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior participated by the online audience;
the self attribute information acquisition module is used for acquiring self attribute information of a live object to be explained in the live broadcast room, and the self attribute information represents the live object attribute information of the live object to be explained;
and the explanation sequence determining module is used for determining the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the attribute information of the live object to be explained.
According to a third aspect of embodiments of the present application, there is provided an electronic apparatus, including: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus; the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the explanation order determination method in the first aspect.
According to a fourth aspect of embodiments of the present application, there is provided a computer storage medium storing a computer program for live interaction, the computer program being stored on a computer storage medium and when executed by a processor, implementing the live object explanation order determination method for a live broadcast room according to the first aspect.
According to a fifth aspect of the embodiments of the present application, a computer program product for live broadcast interaction is provided, where the computer program product includes computer instructions for instructing a computing device to execute operations corresponding to the live broadcast object explanation order determination method in a real-time live broadcast room according to the first aspect.
According to the live broadcast object explanation sequence determining method and device, the electronic equipment and the computer storage medium of the real-time live broadcast room, interactive behavior data corresponding to online audiences in the live broadcast room at the current time period are obtained; obtaining preference attribute information of the online audience based on the analysis of the interactive behavior data; and finally obtaining an explanation sequence of the live objects to be explained based on the obtained matching degree between the preference attribute information and the live object attribute information of each live object to be explained. In the embodiment of the application, in the process of confirming the explanation sequence, the matching degree between preference attribute information analyzed out based on interactive behavior data of online audiences and live broadcasting object attribute information of the live broadcasting object to be explained, therefore, compare with the mode of confirming the explanation sequence depending on artificial experience, the explanation of the live broadcasting object is carried out according to the explanation sequence confirmed by the embodiment of the application, the live broadcasting object of the current explanation can be better matched with the preference of the online audiences, the possibility of purchasing commodities by the online audiences is increased, and the live broadcasting effect is further improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the embodiments of the present application, and other drawings can be obtained by those skilled in the art according to the drawings.
Fig. 1 is a scene schematic diagram of a live broadcast object explanation sequence determination method in a real-time live broadcast room according to an embodiment of the present application;
fig. 2 is a flowchart illustrating steps of a live broadcast object interpretation sequence determination method in a real-time live broadcast room according to an embodiment of the present application;
fig. 3 is a block diagram illustrating a live object interpretation order determination apparatus in a live broadcast room according to a second embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application shall fall within the scope of the protection of the embodiments in the present application.
The following further describes specific implementations of embodiments of the present application with reference to the drawings of the embodiments of the present application.
The first embodiment,
Referring to fig. 1, fig. 1 is a scene schematic diagram of a live object explanation sequence determination method in a real-time live broadcast room according to an embodiment of the present application, and for convenience of understanding, an application scene of the live object explanation sequence determination method in the real-time live broadcast room provided in the embodiment of the present application is first explained with reference to fig. 1.
It should be noted that the live broadcast object explanation sequence determination method in the real-time live broadcast room provided in the embodiment of the present application may be applicable to various types of live broadcast scenes, such as live telecast, education/culture live broadcast, live entertainment/life broadcast, live sports broadcast, and live news broadcast, and the embodiment in fig. 1 is described by taking live telecast as an example.
During the process that the anchor explains the current live broadcast object (for example, a certain man T-shirt), the interactive behavior data of all current online audiences in the live broadcast room can be obtained, such as: clicking commodity link behavior data, commodity adding shopping cart behavior data, comment data and the like; analyzing the interactive behavior data to obtain preference attribute information of the online audience; meanwhile, the self attribute information of the live broadcasting object to be explained in the live broadcasting room is obtained. Based on the matching degree between the preference attribute information of the online audience and the self attribute information of the live object to be explained, the explanation sequence of the live object to be explained is obtained (for example, as shown in fig. 1, there are 4 live objects to be explained, wherein, the woman yoga brick is located at the first position in the explanation sequence), and then, the anchor can perform corresponding operations according to the obtained explanation sequence, for example, as shown in fig. 1: if the anchor is a virtual anchor, the woman yoga bricks can be explained according to the explanation sequence after the man T-shirts are explained; alternatively, if the anchor is a human anchor, the explanation sequence may be output to the anchor so that the anchor may determine a next explanation live object with reference to the explanation sequence. In the embodiment of the application, in the process of confirming the explanation sequence, the matching degree between preference attribute information analyzed out based on interactive behavior data of online audiences and live broadcasting object attribute information of the live broadcasting object to be explained, therefore, compare with the mode of confirming the explanation sequence depending on artificial experience, the explanation of the live broadcasting object is carried out according to the explanation sequence confirmed by the embodiment of the application, the live broadcasting object of the current explanation can be better matched with the preference of the online audiences, the possibility of purchasing commodities by the online audiences is increased, and the live broadcasting effect is further improved.
Referring to fig. 2, fig. 2 is a flowchart illustrating steps of a live object interpretation sequence determination method in a real-time live broadcast room according to an embodiment of the present application; specifically, the live object explanation sequence determining method in the real-time live broadcast room provided by this embodiment includes the following steps:
In the embodiment of the application, the current online audience in the live broadcast room is all online audiences in the live broadcast room in the current time period, or all online audiences entering the live broadcast room in the current time period. The current time period may be a preset time period, such as 3 minutes before the current time, pushed back by the current time.
As described above, the present application may be applied to a live broadcast room in any scene, for example, a live broadcast room in the embodiment of the present application may be a live broadcast room for explaining commodities, a live broadcast room for explaining teaching files, a live broadcast room for explaining news, and the like. If the live broadcast room is a live broadcast room for explaining the commodities, the interaction behavior can include at least one of the following: clicking a commodity link, adding a commodity into a shopping cart, collecting the commodity, ordering the commodity and commenting, wherein the attribute information of the live broadcast object can comprise at least one of the following items: name information, category information, brand information, favorable comment information, deal information, price information. If the live broadcast room is a live broadcast room for explaining teaching files, the interaction behavior can include at least one of the following: favorites, comments, or praise, the live object attribute information may include at least one of: name information, category information, and comment information. If the live broadcast room is a live broadcast room for explaining news, the interaction behavior may include at least one of the following: clicking news links and comments, the attribute information of the live objects can comprise at least one of the following items: name information, category information, and comment information.
In this embodiment of the application, the interactive behavior data may include: real-time interactive behavior data and historical interactive behavior data. The real-time interactive behavior data represent interactive behaviors participated in by online audiences in a first preset time period before the current moment; the historical interaction behavior data represents the interaction behavior of the online audience participating in a second preset time period before the current time; the duration of the first preset time period is less than that of the second preset time period, and the second preset time period comprises the first preset time period.
For example: the real-time interactive behavior data may characterize the interactive behavior of online viewers participating within 3 minutes before the current time; the historical interactive behavior data characterizes the interactive behavior of online viewers engaged in a month prior to the current time.
In addition, before executing the step, whether the preset trigger condition determined aiming at the explanation sequence of the live broadcast object is met or not can be judged, and when the preset trigger condition is met, the step is executed to obtain the interactive behavior data of the current online audience in the live broadcast room.
In the embodiment of the present application, specific contents of the trigger condition are not limited, and may be set according to actual needs, for example: the explanation sequence determination method provided by the embodiment of the present application may be executed periodically according to a preset time period. Correspondingly, the trigger condition may be a time when the current time is a time when the explanation sequence determination method can be executed, or may be actively triggered by the anchor, and when a trigger operation of the anchor is detected, it is determined that the trigger condition is satisfied, or the like.
And step 204, analyzing the interactive behavior data to obtain preference attribute information of the online audience, wherein the preference attribute information is live object attribute information which has a strong association relationship with the interactive behavior participated by the online audience.
Optionally, the interactive behavior data may be parsed to obtain the preference attribute information of the online viewer as follows: analyzing the interaction behavior data to obtain interaction attribute information; the interactive attribute information is live object attribute information related to the interactive behavior of the online audience; and determining preference attribute information of the online audience from all the interaction attribute information based on the quantity of the interaction behavior data associated with each piece of interaction attribute information.
Further, among the interaction attribute information, the interaction attribute information with the largest amount of associated interaction behavior data may be determined as preference attribute information of the online viewer.
Taking the example that the interaction behavior is click commodity link and the attribute information of the live object is commodity name, the interaction behavior data of the click commodity link can be firstly analyzed to determine all commodity links clicked by the online audience, and further determine the commodity name corresponding to the commodity link; if the number of times that a certain commodity link is clicked is the largest, the commodity name corresponding to the commodity link can be determined as preference attribute information of the online audience. Such as: the commodities clicked by the online audience are linked with 4 kinds, respectively: the commodity link of the commodity A, the commodity link of the commodity B, the commodity link of the commodity C and the commodity link of the commodity D, wherein the commodity link of the commodity A is clicked for the most times, and then the commodity A can be determined as a preferred commodity of the online audience.
For another example, assuming that the interactive behavior is comment data, the attribute information of the live object is a product name, the comment data of the online audience may be first subjected to intent analysis to determine all product names related to the comment data, and then, the product name with the most related comment data is determined as a preferred product of the online audience, and so on.
As in step 202 above, the interactive behavior data may include: the real-time interactive behavior data and the historical interactive behavior data, and accordingly, the interactive behavior data is analyzed correspondingly to obtain preference attribute information of the online audience, which may include:
analyzing the real-time interaction behavior data to obtain real-time preference attribute information of the online audience; the real-time preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior of the online audience participating in the first preset time period;
analyzing historical interaction behavior data to obtain historical preference attribute information of online audiences; the historical preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior of the online audience participating in the second preset time period;
and performing information fusion on the real-time preference attribute information and the historical preference attribute information to obtain preference attribute information of the online audience.
Further, performing information fusion on the real-time preference attribute information and the historical preference attribute information to obtain the preference attribute information of the online audience, which may include: and merging the real-time preference attribute information and the historical preference attribute information to obtain the preference attribute information of the online audience.
For example: the obtained real-time preference attribute information is: merchandise A and merchandise B; the obtained historical preference attribute information is: the product A and the product C can be combined with the preference attribute information, and the product A, the product B and the product C are used as the preference attribute information of the online audience.
And step 206, acquiring the self attribute information of the live object to be explained in the live room, wherein the self attribute information represents the live object attribute information of the live object to be explained.
Specifically, there may be a plurality of live objects to be explained in the live room, and in this step, the attribute information of each live object to be explained may be acquired. For example, when the live broadcast object to be explained is a commodity, the attribute information of each commodity may be acquired, such as: one or more of commodity name, commodity category, commodity brand, favorable comment information, deal information, price information, and the like.
And 208, determining the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the attribute information of the live object to be explained.
Specifically, the interpretation order may be determined by an interpretation order prediction model: and inputting the preference attribute information and the self attribute information of the live object to be explained into an explanation sequence prediction model, so that the explanation sequence is predicted to obtain the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the self attribute information of the live object to be explained.
The explanation sequence prediction model may be any one of a linear regression model, a neural network model, a decision tree model, or a machine learning model based on a width and depth architecture.
Optionally, in some embodiments, the live broadcast room may be a live anchor live broadcast room, and correspondingly, after determining an explanation sequence of a live broadcast object to be explained, the live broadcast room may further include: and displaying the determined explanation sequence in a main broadcasting interface of a live broadcasting room so that the real person main broadcasting can refer to the explanation sequence and determine the next explanation live broadcasting object by combining the own live broadcasting experience.
Optionally, in some embodiments, the live broadcast room may also be a virtual anchor live broadcast room, and correspondingly, after the explanation sequence of the live broadcast object to be explained is determined, the method may further include: and enabling the virtual live broadcast of the live broadcast room to explain the live broadcast objects to be explained according to the explanation sequence.
In the embodiment of the application, the interactive behavior data corresponding to the online audience in the live broadcast room in the current time period is acquired, and the preference attribute information of the online audience is acquired based on the analysis of the interactive behavior data; and finally obtaining an explanation sequence of the live objects to be explained based on the obtained matching degree between the preference attribute information and the live object attribute information of each live object to be explained. In the embodiment of the application, the explanation order is determined based on the matching degree between the preference attribute information analyzed through the interactive behavior data of the online audience and the attribute information of the live broadcast object to be explained, therefore, compared with the mode of determining the explanation order by relying on artificial experience, the explanation of the live broadcast object is performed according to the explanation order determined by the embodiment of the application, the live broadcast object to be explained can be better matched with the preference of the online audience, the possibility of purchasing commodities by the online audience is increased, and the live broadcast effect is further improved.
Example II,
Referring to fig. 3, fig. 3 is a block diagram illustrating a live object interpretation order determination apparatus in a real-time live broadcast room according to a second embodiment of the present application. The live broadcast object explanation sequence determining device of the real-time live broadcast room comprises: an interactive behavior data obtaining module 302, configured to obtain interactive behavior data of a current online audience in a live broadcast room, where the interactive behavior data represents an interactive behavior in which the online audience has participated; a preference attribute information obtaining module 304, configured to analyze the interaction behavior data to obtain preference attribute information of the online audience, where the preference attribute information is live object attribute information that has a strong association relationship with an interaction behavior that the online audience has participated in; the self attribute information acquisition module 306 is used for acquiring self attribute information of a live object to be explained in a live broadcast room, wherein the self attribute information represents the live object attribute information of the live object to be explained; and the explanation sequence determining module 308 is configured to determine an explanation sequence of the live object to be explained based on a matching degree between the preference attribute information and the own attribute information of the live object to be explained.
Optionally, in some embodiments, the preference attribute information obtaining module 304 is specifically configured to: analyzing the interactive behavior data to obtain interactive attribute information, wherein the interactive attribute information is live object attribute information associated with the interactive behavior of the online audience; and determining preference attribute information of the online audience from all the interaction attribute information based on the quantity of the interaction behavior data associated with each piece of interaction attribute information.
Optionally, in some embodiments, the preference attribute information obtaining module 304 is specifically configured to, when performing the step of determining the preference attribute information of the online viewer from all the interaction attribute information based on the number of interaction behavior data associated with each piece of interaction attribute information: and determining the interaction attribute information with the maximum quantity of the associated interaction behavior data as the preference attribute information of the online audience.
Optionally, in some embodiments, the explanation order determining module 308 is specifically configured to: and inputting the preference attribute information and the self attribute information of the live object to be explained into an explanation sequence prediction model, so that the explanation sequence is predicted to obtain the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the self attribute information of the live object to be explained.
Optionally, in some of the embodiments, the order prediction model is one of a linear regression model, a neural network model, a decision tree model, or a machine learning model based on a width and depth architecture.
Optionally, in some embodiments, the live broadcast room is a live anchor live broadcast room, and the explanation order determining apparatus further includes: and the display module is used for displaying the explanation sequence in a main broadcasting interface of the live broadcasting room after the explanation sequence of the live broadcasting object to be explained is determined.
Optionally, in some embodiments, the live broadcast room is a virtual anchor live broadcast room, and the explanation order determining apparatus further includes: and the automatic explanation module is used for enabling the virtual live broadcast of the live broadcast room to explain the live broadcast objects to be explained according to the explanation sequence after the explanation sequence of the live broadcast objects to be explained is determined.
Optionally, in some embodiments, the interaction behavior data obtaining module 302 is specifically configured to: judging whether the current condition meets a preset trigger condition determined aiming at the explanation sequence of the live objects; and if so, acquiring the interactive behavior data of the current online audience in the live broadcast room.
Optionally, in some embodiments, the live object to be explained is a commodity; the interaction behavior comprises at least one of the following: clicking a commodity link, adding a commodity into a shopping cart, collecting the commodity, ordering the commodity and commenting; the live object attribute information includes at least one of: name information, category information, brand information, favorable comment information, deal information, price information.
Optionally, in some embodiments, the live object to be explained is a teaching file; the interaction behavior comprises at least one of the following: collection, review, or like; the live object attribute information includes at least one of: name information, category information, and comment information.
Optionally, in some of these embodiments, the interactive behavior data includes: real-time interactive behavior data and historical interactive behavior data; the real-time interactive behavior data represent interactive behaviors participated in by online audiences in a first preset time period before the current moment; the historical interaction behavior data represents the interaction behavior of the online audience participating in a second preset time period before the current time; the duration of the first preset time period is less than the duration of the second preset time period; the second preset time period comprises the first preset time period.
Optionally, in some embodiments, the preference attribute information obtaining module 304 is specifically configured to: analyzing the real-time interactive behavior data to obtain real-time preference attribute information of the online audience, wherein the real-time preference attribute information is live object attribute information which has a strong association relation with the interactive behavior of the online audience participating in the first preset time period; analyzing historical interaction behavior data to obtain historical preference attribute information of the online audience, wherein the historical preference attribute information is live object attribute information which has a strong association relation with the interaction behavior of the online audience participating in the second preset time period; and performing information fusion on the real-time preference attribute information and the historical preference attribute information to obtain preference attribute information of the online audience.
Optionally, in some embodiments, the preference attribute information obtaining module 304 is specifically configured to, when performing the step of performing information fusion on the real-time preference attribute information and the historical preference attribute information to obtain the preference attribute information of the online viewer: and merging the real-time preference attribute information and the historical preference attribute information to obtain the preference attribute information of the online audience.
The explanation sequence determining apparatus of this embodiment is used to implement the corresponding explanation sequence determining method in the foregoing method embodiments, and has the beneficial effects of the corresponding method embodiments, and will not be described herein again. In addition, the functional implementation of each module in the explanation order determination apparatus of this embodiment can refer to the description of the corresponding part in the foregoing method embodiment, and is not repeated here.
Example III,
Referring to fig. 4, a schematic structural diagram of an electronic device according to a third embodiment of the present application is shown, and the specific embodiment of the present application does not limit a specific implementation of the electronic device.
As shown in fig. 4, the electronic device may include: a processor (processor)402, a Communications Interface 404, a memory 406, and a Communications bus 408. The processor 402, communication interface 404, and memory 406 communicate with each other via a communication bus 408. The communication interface 404 is used for communication with other electronic devices or servers. The processor 402 is used for executing the program 410, and may specifically execute the relevant steps in the above-described explanation order determination method embodiment. In particular, program 410 may include program code comprising computer operating instructions.
The processor 402 may be a CPU, or an application Specific Integrated circuit (asic), or one or more Integrated circuits configured to implement embodiments of the present application. The intelligent device comprises one or more processors which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
The memory 406 is used to store a program 410. The memory 706 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 410 may specifically be configured to cause the processor 402 to perform the following operations: acquiring interactive behavior data of current online audiences in a live broadcast room; the interactive behavior data characterizes interactive behaviors that the online audience has participated in; analyzing the interactive behavior data to obtain preference attribute information of the online audience; the preference attribute information is live broadcast object attribute information which has a strong association relation with the interactive behavior participated by the online audience; acquiring self attribute information of a live object to be explained in a live broadcast room, wherein the self attribute information represents the live object attribute information of the live object to be explained; and determining the explanation sequence of the live objects to be explained based on the matching degree between the preference attribute information and the attribute information of the live objects to be explained.
For specific implementation of each step in the program 410, reference may be made to corresponding steps and corresponding descriptions in units in the foregoing embodiment of the live broadcast object explanation sequence determination method in the real-time live broadcast room, which are not described herein again. It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described devices and modules may refer to the corresponding process descriptions in the foregoing method embodiments, and are not described herein again.
Acquiring interactive behavior data corresponding to online audiences in a live broadcast room at the current time period by the electronic equipment of the embodiment; obtaining preference attribute information of the online audience based on the analysis of the interactive behavior data; and finally obtaining an explanation sequence of the live objects to be explained based on the obtained matching degree between the preference attribute information and the live object attribute information of each live object to be explained. In the embodiment of the application, in the process of confirming the explanation sequence, the matching degree between preference attribute information analyzed out based on interactive behavior data of online audiences and live broadcasting object attribute information of the live broadcasting object to be explained, therefore, compare with the mode of confirming the explanation sequence depending on artificial experience, the explanation of the live broadcasting object is carried out according to the explanation sequence confirmed by the embodiment of the application, the live broadcasting object of the current explanation can be better matched with the preference of the online audiences, the possibility of purchasing commodities by the online audiences is increased, and the live broadcasting effect is further improved.
The embodiment of the present application further provides a computer storage medium storing a computer program for determining a live object explanation sequence of a real-time live broadcast room, where the computer program is stored on the computer storage medium, and when executed by a processor, the computer program implements a live object explanation sequence determination method of any one of the multiple method embodiments.
The embodiment of the present application further provides a computer program product for determining a live object explanation sequence in a real-time live broadcast room, where the computer program product includes a computer instruction that instructs a computing device to execute an operation corresponding to a live object explanation sequence determination method in any of the multiple method embodiments.
It should be noted that, according to the implementation requirement, each component/step described in the embodiment of the present application may be divided into more components/steps, and two or more components/steps or partial operations of the components/steps may also be combined into a new component/step to achieve the purpose of the embodiment of the present application.
The above-described methods according to embodiments of the present application may be implemented in hardware, firmware, or as software or computer code storable in a recording medium such as a CD ROM, a RAM, a floppy disk, a hard disk, or a magneto-optical disk, or as computer code originally stored in a remote recording medium or a non-transitory machine-readable medium downloaded through a network and to be stored in a local recording medium, so that the methods described herein may be stored in such software processes on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware such as an ASIC or FPGA. It will be appreciated that the computer, processor, microprocessor controller or programmable hardware includes memory components (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the live object interpretation sequence determination method described herein for a real-time live broadcast room. Further, when a general-purpose computer accesses code for implementing the live object explanation order determination method of the real-time live broadcast room shown here, execution of the code converts the general-purpose computer into a special-purpose computer for executing the live object explanation order determination method of the real-time live broadcast room shown here.
Those of ordinary skill in the art will appreciate that the various illustrative elements and method steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the embodiments of the present application.
The above embodiments are only used for illustrating the embodiments of the present application, and not for limiting the embodiments of the present application, and those skilled in the relevant art can make various changes and modifications without departing from the spirit and scope of the embodiments of the present application, so that all equivalent technical solutions also belong to the scope of the embodiments of the present application, and the scope of patent protection of the embodiments of the present application should be defined by the claims.
Claims (14)
1. A live broadcast object explanation sequence determination method of a real-time live broadcast room comprises the following steps:
acquiring interactive behavior data of current online audiences in a live broadcast room; the interactive behavior data characterizes interactive behaviors that the online audience has participated in;
analyzing the interaction behavior data to obtain preference attribute information of online audiences; the preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior participated by the online audience;
acquiring self attribute information of a live object to be explained in the live broadcast room, wherein the self attribute information represents the live object attribute information of the live object to be explained;
and determining the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the attribute information of the live object to be explained.
2. The method of claim 1, wherein the parsing the interaction behavior data to obtain preference attribute information of online viewers comprises:
analyzing the interaction behavior data to obtain interaction attribute information; the interaction attribute information is live object attribute information associated with the interaction behavior of the online audience;
and determining preference attribute information of the online audience from all the interaction attribute information based on the quantity of the interaction behavior data associated with each piece of interaction attribute information.
3. The method of claim 2, wherein the determining preference attribute information of the online viewer from all the interaction attribute information based on the amount of interaction behavior data associated with each interaction attribute information comprises:
and determining the interaction attribute information with the maximum quantity of the associated interaction behavior data as the preference attribute information of the online audience.
4. The method according to any one of claims 1 to 3, wherein the determining the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the own attribute information of the live object to be explained comprises:
inputting the preference attribute information and the attribute information of the live object to be explained into an explanation sequence prediction model, so that the explanation sequence is predicted to obtain the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the attribute information of the live object to be explained.
5. The method of claim 1, wherein the live room is a live anchor live room;
after the determining the explanation sequence of the live object to be explained, the method further comprises:
and displaying the explanation sequence in a main broadcasting interface of the live broadcasting room.
6. The method of claim 1, wherein the live room is a virtual anchor live room;
after the determining the explanation sequence of the live object to be explained, the method further comprises:
and enabling the virtual live broadcast of the live broadcast room to explain the live broadcast object to be explained according to the explanation sequence.
7. The method of claim 1, wherein the obtaining of interactive behavior data of a currently online audience in a live room comprises:
judging whether the current condition meets a preset trigger condition determined aiming at the explanation sequence of the live objects;
and if so, acquiring the interactive behavior data of the current online audience in the live broadcast room.
8. The method according to claim 1, wherein the live object to be explained is a commodity; the interaction behavior comprises at least one of: clicking a commodity link, adding a commodity into a shopping cart, collecting the commodity, ordering the commodity and commenting; the live object attribute information includes at least one of: name information, category information, brand information, favorable comment information, deal information, price information.
9. The method of claim 1, wherein the live object to be explained is an instructional file; the interaction behavior comprises at least one of: collection, review, or like; the live object attribute information includes at least one of: name information, category information, and comment information.
10. The method of claim 1, wherein the interactive behavior data comprises: real-time interactive behavior data and historical interactive behavior data; the real-time interactive behavior data represents the interactive behavior of the online audience participating in a first preset time period before the current moment; the historical interaction behavior data represents the interaction behavior of the online audience participating in a second preset time period before the current time; the duration of the first preset time period is less than the duration of the second preset time period; the second preset time period comprises the first preset time period;
analyzing the interaction behavior data to obtain preference attribute information of the online audience, wherein the preference attribute information comprises:
analyzing the real-time interaction behavior data to obtain real-time preference attribute information of the online audience; the real-time preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior of the online audience participating in the first preset time period;
analyzing the historical interaction behavior data to obtain historical preference attribute information of the online audience; the historical preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior of the online audience participating in the second preset time period;
and merging the real-time preference attribute information and the historical preference attribute information to obtain the preference attribute information of the online audience.
11. A live object interpretation order determination apparatus of a real-time live broadcast room, comprising:
the interactive behavior data acquisition module is used for acquiring the interactive behavior data of the current online audience in the live broadcast room; the interactive behavior data characterizes interactive behaviors that the online audience has participated in;
the preference attribute information obtaining module is used for analyzing the interaction behavior data to obtain preference attribute information of the online audience; the preference attribute information is live broadcast object attribute information which has a strong association relationship with the interactive behavior participated by the online audience;
the self attribute information acquisition module is used for acquiring self attribute information of a live object to be explained in the live broadcast room, and the self attribute information represents the live object attribute information of the live object to be explained;
and the explanation sequence determining module is used for determining the explanation sequence of the live object to be explained based on the matching degree between the preference attribute information and the attribute information of the live object to be explained.
12. An electronic device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the live object explanation sequence determination method of the real-time live broadcast room in any one of claims 1-10.
13. A computer storage medium having stored thereon a computer program for determining a live object interpretation order of a real time live broadcast room, which program, when executed by a processor, implements a live object interpretation order determination method of a real time live broadcast room as claimed in any one of claims 1-10.
14. A computer program product for determining a live object interpretation order of a real-time live broadcast room, comprising computer instructions for instructing a computing device to perform operations corresponding to the live object interpretation order determination method of the real-time live broadcast room as claimed in any one of claims 1 to 10.
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| CN202210008539.6A CN114357305A (en) | 2022-01-05 | 2022-01-05 | Live broadcast object explanation sequence determination method and device of real-time live broadcast room |
| PCT/CN2022/143620 WO2023131056A1 (en) | 2022-01-05 | 2022-12-29 | Method and device for determining live streaming object introduction order in real-time live streaming room |
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| CN202210008539.6A CN114357305A (en) | 2022-01-05 | 2022-01-05 | Live broadcast object explanation sequence determination method and device of real-time live broadcast room |
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| CN117135379A (en) * | 2023-10-26 | 2023-11-28 | 武汉耳东信息科技有限公司 | Live broadcast platform data analysis management system based on big data |
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| CN117135370B (en) * | 2023-10-26 | 2024-02-06 | 深圳企域数字科技有限公司 | AIGC-based live broadcasting room operation regulation and control method and system |
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| WO2023131056A1 (en) | 2023-07-13 |
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