CN116340813A - User behavior analysis system and method for live platform - Google Patents

User behavior analysis system and method for live platform Download PDF

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Publication number
CN116340813A
CN116340813A CN202310154812.0A CN202310154812A CN116340813A CN 116340813 A CN116340813 A CN 116340813A CN 202310154812 A CN202310154812 A CN 202310154812A CN 116340813 A CN116340813 A CN 116340813A
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data
standard
interaction
behavior
invalid
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CN202310154812.0A
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CN116340813B (en
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陈军
陈凯
庄汇达
陈银银
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Guangzhou Netyouyou Data Technology Co ltd
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Shenzhen Kuaimei Cosmetics Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/21—Server components or server architectures
    • H04N21/218—Source of audio or video content, e.g. local disk arrays
    • H04N21/2187—Live feed
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/475—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data
    • H04N21/4756—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data for rating content, e.g. scoring a recommended movie
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/478—Supplemental services, e.g. displaying phone caller identification, shopping application
    • H04N21/4788—Supplemental services, e.g. displaying phone caller identification, shopping application communicating with other users, e.g. chatting
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The invention provides a user behavior analysis system and method for a live broadcast platform. The cloud server acquires the historical live broadcasting behavior data of the live broadcasting room and the historical live broadcasting room data of the live broadcasting room from a plurality of live broadcasting edge servers according to a preset rule, and correspondingly acquires the historical interaction behavior data of audience of the live broadcasting room from a plurality of play edge servers; based on the time sequence, establishing an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data; generating an invalid interactive behavior portrait, a standard interactive behavior portrait and a standard shopping behavior portrait according to the historical interactive behavior data; and generating a standard live behavior portrait according to the association relation and the standard shopping portrait. By the scheme of the invention, the standard live broadcast guide can be obtained based on the interaction behavior of the live broadcast room, and the live broadcast efficiency can be effectively improved in time.

Description

User behavior analysis system and method for live platform
Technical Field
The invention relates to the technical field of live broadcasting, in particular to a user behavior analysis system and method for a live broadcasting platform.
Background
With the development of internet technology and the improvement of data transmission, video live broadcast technology has been very popular, and network live broadcast becomes an emerging network social mode, and has wide application in the fields of life, entertainment, consumption and the like of people.
In the live video delivery process, the live broadcast effect of the host and the operation team plays a decisive role in the live video delivery process, and in order to know the relationship between each behavior of the host and other relevant live broadcast subjects and the live video delivery effect, the behaviors of each participant in the live video delivery room need to be analyzed, in particular, the relationship between the key behaviors of the host and the successful sales results is analyzed. However, the existing method relies on manual experience to analyze the behavior data of the live broadcast participants, and the method is time-consuming, labor-consuming and easily affected by subjective bias due to excessive interaction data among users of the platform.
Disclosure of Invention
Based on the above problems, the invention provides a user behavior analysis system and method for a live broadcast platform, and by the scheme of the invention, standard live broadcast guidance can be obtained based on interaction behavior of a live broadcast room, and live broadcast efficiency can be effectively improved in time.
In view of this, an aspect of the present invention proposes a user behavior analysis system for a live platform, comprising: the system comprises a plurality of live broadcast edge servers, a cloud server, a plurality of play edge servers and a plurality of play terminals; wherein, the liquid crystal display device comprises a liquid crystal display device,
the cloud server is configured to:
acquiring historical live broadcasting behavior data of a live broadcasting room and historical live broadcasting room data of the live broadcasting room from the plurality of live broadcasting edge servers according to preset rules, wherein the historical live broadcasting behavior data comprise anchor action data, anchor dressing data, anchor voice data and virtual dressing data, and the historical live broadcasting room data comprise historical online people, historical environment data, historical background sound data and historical advertisement putting data;
correspondingly acquiring historical interaction behavior data of audiences in the live broadcasting room from the plurality of play edge servers, wherein the historical interaction behavior data comprise expression data, gesture data, bullet screen data, virtual gift data, praying data, click advertisement data, shopping cart data and commodity purchasing data;
based on a time sequence, establishing an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data;
Generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data;
and generating a standard live behavior portrait according to the association relation and the standard shopping portrait.
Optionally, the cloud server is further configured to:
the cloud server selects a first direct broadcast edge server from the plurality of direct broadcast edge servers;
the cloud server acquires first direct broadcast video data of a first main broadcast between first direct broadcast and first live broadcast room data of the first live broadcast room from the first direct broadcast edge server;
judging whether the live behavior of the first host and/or the arrangement of the first live broadcasting room meets the current live broadcasting requirement according to the standard live broadcasting behavior portrait, the first live broadcasting room data and the first live broadcasting video data;
if yes, integrating the first direct broadcast video data and the first live broadcasting room data into first direct broadcast data, sending the first direct broadcast data to a corresponding first playing edge server in the plurality of playing edge servers, and forwarding the first direct broadcast video data and the first direct broadcast data to the plurality of playing terminals or the first playing terminals in the plurality of playing terminals by the first playing edge server;
If the video data does not accord with the standard live broadcast behavior portraits, outputting an improvement suggestion, or modifying the first live broadcast video data and the first live broadcast room data according to the standard live broadcast behavior portraits, integrating to obtain second live broadcast data, sending the second live broadcast data to the corresponding first playing edge server in the playing edge servers, and forwarding the second live broadcast data to the playing terminals or the first playing terminals in the playing terminals by the first playing edge server.
Optionally, the cloud server is further configured to:
acquiring first interaction behavior data of audience of the first living broadcast room;
determining invalid interaction audiences according to the invalid interaction behavior portraits and the first interaction behavior data, and taking invalid interaction corresponding measures for the interaction behaviors of the invalid interaction audiences;
determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking standard interaction corresponding measures for the interaction behaviors of the standard interaction audience;
and determining a shopping interaction audience by the standard shopping behavior portrait and the first interaction behavior data, and taking shopping interaction countermeasure for the interaction behavior of the shopping interaction audience.
Optionally, in the step of determining an invalid interaction audience according to the invalid interaction behavior portrait and the first interaction behavior data and taking an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience, the cloud server is specifically configured to:
the bullet screen data and comment data are proposed from the first interactive behavior data, and the first invalid bullet screen data and the first invalid comment data are determined according to the invalid interactive behavior portraits;
according to the relevance of the context, combining the first invalid barrage data and the first invalid comment data to determine second invalid barrage data and second invalid comment data;
determining corresponding bullet screen senders and comment outputters according to the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data, and determining the bullet screen senders and the comment outputters as the invalid interaction audience;
aiming at the interaction behaviors of the invalid interaction audience, optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data;
And pre-examining the follow-up interaction behavior of the invalid interaction audience, judging whether the follow-up interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience.
Optionally, in the step of determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data and taking standard interaction countermeasure for the interaction behavior of the standard interaction audience, the cloud server is specifically configured to:
extracting gift virtual gift data, praise data and click advertisement data from the first interaction behavior data;
determining first standard barrage data, first standard comment data, first standard presentation virtual gift data, first standard approval data and first standard click advertisement data according to the standard interaction behavior portrait, the barrage data, the comment data, the presentation virtual gift data, the approval data and the click advertisement data;
according to the relevance of the context, combining the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data and the first standard click advertisement data to determine second standard barrage data, second standard comment data, second standard gifting virtual gift data, second standard praise data and second standard click advertisement data;
Determining the standard interactive audience according to the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data, the first standard click advertisement data, the second standard barrage data, the second standard comment data, the second standard gifting virtual gift data, the second standard praise data and the second standard click advertisement data;
acquiring character feature data of the standard interactive audience, and acquiring character portrait data according to the character feature data;
and according to the character portrait data, the interaction behavior of the standard interaction audience is interacted, so that commodity purchase of the standard interaction audience is promoted.
Another aspect of the present invention provides a user behavior analysis method for a live platform, applied to a user behavior analysis system for a live platform, the user behavior analysis system for a live platform including a plurality of live edge servers, a cloud server, a plurality of play edge servers, and a plurality of play terminals, the method comprising:
the cloud server acquires historical live broadcasting behavior data of a live broadcasting room and historical live broadcasting room data of the live broadcasting room from the plurality of live broadcasting edge servers according to preset rules, wherein the historical live broadcasting behavior data comprise anchor action data, anchor dressing data, anchor voice data and virtual dressing data, and the historical live broadcasting room data comprise historical online people, historical environment data, historical background sound data and historical advertisement putting data;
The cloud server correspondingly acquires historical interaction behavior data of audiences in the live broadcasting room from the plurality of play edge servers, wherein the historical interaction behavior data comprise expression data, gesture data, bullet screen data, virtual gift data, praise data, advertisement clicking data, shopping cart data and commodity purchasing data;
based on a time sequence, establishing an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data;
generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data;
and generating a standard live behavior portrait according to the association relation and the standard shopping portrait.
Optionally, the method further comprises:
the cloud server selects a first direct broadcast edge server from the plurality of direct broadcast edge servers;
the cloud server acquires first direct broadcast video data of a first main broadcast between first direct broadcast and first live broadcast room data of the first live broadcast room from the first direct broadcast edge server;
judging whether the live behavior of the first host and/or the arrangement of the first live broadcasting room meets the current live broadcasting requirement according to the standard live broadcasting behavior portrait, the first live broadcasting room data and the first live broadcasting video data;
If yes, integrating the first direct broadcast video data and the first live broadcasting room data into first direct broadcast data, sending the first direct broadcast data to a corresponding first playing edge server in the plurality of playing edge servers, and forwarding the first direct broadcast video data and the first direct broadcast data to the plurality of playing terminals or the first playing terminals in the plurality of playing terminals by the first playing edge server;
if the video data does not accord with the standard live broadcast behavior portraits, outputting an improvement suggestion, or modifying the first live broadcast video data and the first live broadcast room data according to the standard live broadcast behavior portraits, integrating to obtain second live broadcast data, sending the second live broadcast data to the corresponding first playing edge server in the playing edge servers, and forwarding the second live broadcast data to the playing terminals or the first playing terminals in the playing terminals by the first playing edge server.
Optionally, the method further comprises:
the cloud server acquires first interaction behavior data of audience of the first live broadcasting room;
determining invalid interaction audiences according to the invalid interaction behavior portraits and the first interaction behavior data, and taking invalid interaction corresponding measures for the interaction behaviors of the invalid interaction audiences;
Determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking standard interaction corresponding measures for the interaction behaviors of the standard interaction audience;
and determining a shopping interaction audience by the standard shopping behavior portrait and the first interaction behavior data, and taking shopping interaction countermeasure for the interaction behavior of the shopping interaction audience.
Optionally, the step of determining an invalid interaction audience according to the invalid interaction behavior portrait and the first interaction behavior data and taking an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience includes:
the bullet screen data and comment data are proposed from the first interactive behavior data, and the first invalid bullet screen data and the first invalid comment data are determined according to the invalid interactive behavior portraits;
according to the relevance of the context, combining the first invalid barrage data and the first invalid comment data to determine second invalid barrage data and second invalid comment data;
determining corresponding bullet screen senders and comment outputters according to the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data, and determining the bullet screen senders and the comment outputters as the invalid interaction audience;
Aiming at the interaction behaviors of the invalid interaction audience, optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data;
and pre-examining the follow-up interaction behavior of the invalid interaction audience, judging whether the follow-up interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience.
Optionally, the step of determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data and taking standard interaction countermeasure for the interaction behavior of the standard interaction audience includes:
extracting gift virtual gift data, praise data and click advertisement data from the first interaction behavior data;
determining first standard barrage data, first standard comment data, first standard presentation virtual gift data, first standard approval data and first standard click advertisement data according to the standard interaction behavior portrait, the barrage data, the comment data, the presentation virtual gift data, the approval data and the click advertisement data;
According to the relevance of the context, combining the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data and the first standard click advertisement data to determine second standard barrage data, second standard comment data, second standard gifting virtual gift data, second standard praise data and second standard click advertisement data;
determining the standard interactive audience according to the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data, the first standard click advertisement data, the second standard barrage data, the second standard comment data, the second standard gifting virtual gift data, the second standard praise data and the second standard click advertisement data;
acquiring character feature data of the standard interactive audience, and acquiring character portrait data according to the character feature data;
and according to the character portrait data, the interaction behavior of the standard interaction audience is interacted, so that commodity purchase of the standard interaction audience is promoted.
By adopting the technical scheme of the invention, the user behavior analysis system for the live broadcast platform is provided with a plurality of live broadcast edge servers, a cloud server, a plurality of play edge servers and a plurality of play terminals. The cloud server acquires historical live broadcasting behavior data of a live broadcasting room and historical live broadcasting room data of the live broadcasting room from the plurality of live broadcasting edge servers according to preset rules, correspondingly acquires historical interaction behavior data of audiences of the live broadcasting room from the plurality of play edge servers, and establishes an association relationship among the historical live broadcasting behavior data, the historical live broadcasting room data and the historical interaction behavior data based on a time sequence; generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data; and generating a standard live behavior portrait according to the association relation and the standard shopping portrait. By the scheme provided by the embodiment of the invention, the standard live broadcast guide can be obtained based on the interaction behavior of the live broadcast room, and the live broadcast efficiency can be effectively improved in time.
Drawings
FIG. 1 is a schematic block diagram of a user behavior analysis system for a live platform provided in one embodiment of the invention;
Fig. 2 is a flowchart of a user behavior analysis method for a live platform according to an embodiment of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced otherwise than as described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
A user behavior analysis system and method for a live platform according to some embodiments of the present invention are described below with reference to fig. 1-2.
As shown in fig. 1, one embodiment of the present invention provides a user behavior analysis system for a live platform, including: the system comprises a plurality of live broadcast edge servers, a cloud server, a plurality of play edge servers and a plurality of play terminals; wherein, the liquid crystal display device comprises a liquid crystal display device,
the cloud server is configured to:
acquiring historical live broadcasting behavior data of a live broadcasting room and historical live broadcasting room data of the live broadcasting room from the plurality of live broadcasting edge servers according to preset rules, wherein the historical live broadcasting behavior data comprise anchor action data, anchor dressing data, anchor voice data and virtual dressing data, and the historical live broadcasting room data comprise historical online people, historical environment data, historical background sound data and historical advertisement putting data;
Correspondingly acquiring historical interaction behavior data of audiences in the live broadcasting room from the plurality of play edge servers, wherein the historical interaction behavior data comprise expression data, gesture data, bullet screen data, virtual gift data, praying data, click advertisement data, shopping cart data and commodity purchasing data;
based on a time sequence, establishing an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data;
generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data;
and generating a standard live behavior portrait according to the association relation and the standard shopping portrait.
It may be understood that in this embodiment, the live edge server is disposed at a side closer to the live camera system, and is configured to perform preliminary processing on data transmitted by the live camera system, which may be an internet of things server; the cloud server is used for comprehensively managing the live broadcast edge server and the play edge server, and carrying out deep processing and universality processing on data; the playing edge server is arranged on the side closer to the playing terminal and is used for carrying out adaptability processing on data sent to the playing terminal or sent by the playing terminal; the playing terminal is used for users/spectators to watch live video and participate in live interaction through the live client.
It should be noted that, generating invalid interactive behavior portraits, standard interactive behavior portraits and standard shopping behavior portraits according to the historical interactive behavior data is specifically:
inputting the historical interaction behavior data into a trained behavior classification model to obtain invalid interaction behavior data, standard interaction behavior data and standard shopping behavior data;
respectively carrying out feature processing on the invalid interaction behavior data, the standard interaction behavior data and the standard shopping behavior data, and generating N invalid interaction behavior feature data sets, N standard interaction behavior feature data sets and N standard shopping behavior feature data sets based on N preset different feature dimensions;
and constructing invalid interactive behavior portraits, standard interactive behavior portraits and standard shopping behavior portraits according to the N invalid interactive behavior feature data sets, the N standard interactive behavior feature data sets and the N standard shopping behavior feature data sets.
The following will exemplify only the construction flow of the invalid interactive behavior portrayal, and the construction of the standard interactive behavior portrayal and the standard shopping behavior portrayal are the same.
The construction flow of the invalid interactive behavior portrait is as follows:
Generating an invalid interaction behavior feature model by utilizing the N invalid interaction behavior feature data sets;
performing data fusion after performing standardized processing on the N invalid interaction behavior feature data sets to obtain first feature data;
processing the first characteristic data by using the invalid interaction behavior characteristic model to obtain evaluation data based on the preset N different characteristic dimensions;
constructing the invalid interactive behavior portrait by using the evaluation data;
wherein N is a positive integer.
In the embodiment of the invention, the cloud server acquires the historical live broadcast behavior data of a live broadcast room and the historical live broadcast room data of the live broadcast room from the plurality of live broadcast edge servers according to preset rules (such as a designated area range, a designated time period, a designated main broadcasting style, a designated live broadcast content type and the like), correspondingly acquires the historical interaction behavior data of a spectator of the live broadcast room from the plurality of play edge servers, and establishes an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data based on a time sequence; generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data; and generating a standard live behavior portrait according to the association relation and the standard shopping portrait. By the scheme provided by the embodiment of the invention, the standard live broadcast guide can be obtained based on the interaction behavior of the live broadcast room, and the live broadcast efficiency can be effectively improved in time.
It should be noted that the block diagram of the user behavior analysis system for a live platform shown in fig. 1 is only illustrative, and the number of modules shown is not limiting on the scope of the present invention.
In some possible embodiments of the present invention, the cloud server is further configured to:
the cloud server selects a first direct broadcast edge server from the plurality of direct broadcast edge servers;
the cloud server acquires first direct broadcast video data of a first main broadcast between first direct broadcast and first live broadcast room data of the first live broadcast room from the first direct broadcast edge server;
judging whether the live behavior of the first host and/or the arrangement of the first live broadcasting room meets the current live broadcasting requirement according to the standard live broadcasting behavior portrait, the first live broadcasting room data and the first live broadcasting video data;
if yes, integrating the first direct broadcast video data and the first live broadcasting room data into first direct broadcast data, sending the first direct broadcast data to a corresponding first playing edge server in the plurality of playing edge servers, and forwarding the first direct broadcast video data and the first direct broadcast data to the plurality of playing terminals or the first playing terminals in the plurality of playing terminals by the first playing edge server;
If the video data does not accord with the standard live broadcast behavior portraits, outputting an improvement suggestion, or modifying the first live broadcast video data and the first live broadcast room data according to the standard live broadcast behavior portraits, integrating to obtain second live broadcast data, sending the second live broadcast data to the corresponding first playing edge server in the playing edge servers, and forwarding the second live broadcast data to the playing terminals or the first playing terminals in the playing terminals by the first playing edge server.
It may be appreciated that, in order to make the live action of the host and the decoration/rendering effect of the live room (such as the aspects of environment and background music) better conform to the live content, the commodity, the viewer preference, etc., in this embodiment, it is determined whether the current live action/live room arrangement conforms to the current live demand, if not, an improvement suggestion (such as an improvement suggestion on the aspects of the action, the mood, the dressing, the virtual video rendering of the live room, the background music, etc. of the first host) is output, or, after the first live action representation is modified, the first live video data and the first live room data are intelligently and automatically modified through an algorithm preset by a cloud server, so as to integrate to obtain second live data, and the second live data is sent to the corresponding first play border server in the plurality of play border servers, and is forwarded to the plurality of play terminals or the first play terminal in the plurality of play terminals by the first play border server.
In some possible embodiments of the present invention, the cloud server is further configured to:
acquiring first interaction behavior data of audience of the first living broadcast room;
determining invalid interaction audiences according to the invalid interaction behavior portraits and the first interaction behavior data, and taking invalid interaction corresponding measures for the interaction behaviors of the invalid interaction audiences;
determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking standard interaction corresponding measures for the interaction behaviors of the standard interaction audience;
and determining a shopping interaction audience by the standard shopping behavior portrait and the first interaction behavior data, and taking shopping interaction countermeasure for the interaction behavior of the shopping interaction audience.
It may be appreciated that, in order to improve the effectiveness of the interaction behavior of the live broadcasting room, in this embodiment, the cloud server determines, according to the invalid interaction behavior representation, the standard interaction behavior representation and the first interaction behavior data, an invalid interaction audience, a standard interaction audience and a shopping interaction audience, and respectively takes an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience, a standard interaction countermeasure for the interaction behavior of the standard interaction audience, and a shopping interaction countermeasure for the interaction behavior of the shopping interaction audience, so as to interact with different types of audience in a targeted manner, thereby improving interaction efficiency.
In some possible embodiments of the present invention, in the step of determining an invalid interaction audience according to the invalid interaction portraits and the first interaction behavior data and taking an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience, the cloud server is specifically configured to:
the bullet screen data and comment data are proposed from the first interactive behavior data, and the first invalid bullet screen data and the first invalid comment data are determined according to the invalid interactive behavior portraits;
according to the relevance of the context, combining the first invalid barrage data and the first invalid comment data to determine second invalid barrage data and second invalid comment data;
determining corresponding bullet screen senders and comment outputters according to the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data, and determining the bullet screen senders and the comment outputters as the invalid interaction audience;
aiming at the interaction behaviors of the invalid interaction audience, optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data;
And pre-examining the follow-up interaction behavior of the invalid interaction audience, judging whether the follow-up interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience.
It can be understood that management of invalid interaction behaviors is enhanced, negative effects of malicious interaction behaviors are eliminated, in this embodiment, invalid interaction data in first interaction behavior data is determined according to the invalid interaction behavior portrait, and according to relevance of context, associated invalid interaction behavior data is extracted, and then invalid interaction spectators are determined. Optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data (such as shielding inequality words/images, automatically adding interpretation reply words and the like) aiming at the interaction behaviors of the invalid interaction audience; and pre-examining the subsequent interaction behavior of the invalid interaction audience, judging whether the subsequent interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience, namely limiting the operation of the invalid interaction audience on a live broadcast client.
In some possible embodiments of the present invention, in the step of determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking a standard interaction countermeasure for the interaction behavior of the standard interaction audience, the cloud server is specifically configured to:
extracting gift virtual gift data, praise data and click advertisement data from the first interaction behavior data;
determining first standard barrage data, first standard comment data, first standard presentation virtual gift data, first standard approval data and first standard click advertisement data according to the standard interaction behavior portrait, the barrage data, the comment data, the presentation virtual gift data, the approval data and the click advertisement data;
according to the relevance of the context, combining the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data and the first standard click advertisement data to determine second standard barrage data, second standard comment data, second standard gifting virtual gift data, second standard praise data and second standard click advertisement data;
Determining the standard interactive audience according to the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data, the first standard click advertisement data, the second standard barrage data, the second standard comment data, the second standard gifting virtual gift data, the second standard praise data and the second standard click advertisement data;
acquiring character feature data of the standard interactive audience, and acquiring character portrait data according to the character feature data;
and according to the character portrait data, the interaction behavior of the standard interaction audience is interacted, so that commodity purchase of the standard interaction audience is promoted.
It can be understood that, in order to promote the transformation of the interaction behavior in the live broadcasting room and improve the positive effect of the live broadcasting, the audience (i.e. the standard interaction audience) watching the live broadcasting in the live broadcasting room and having no negative emotion but not strong purchase intention is subjected to the focused and targeted interaction, in this embodiment, the standard interaction behavior data is selected from the first interaction behavior data according to the standard interaction behavior portrait, and after the standard interaction audience is further determined, the character feature data of the standard interaction audience is obtained, and the character portrait data is obtained according to the character feature data; and according to the figure data, the interaction behavior of the standard interaction audience is interacted (such as pushing commodity functions which can feel interest, pushing commodity combinations which can feel interest and benefit and meet the requirements according to the figure characteristic key/introduction, and the like) so as to promote the standard interaction audience to purchase commodities.
Referring to fig. 2, another embodiment of the present invention provides a user behavior analysis method for a live platform, which is applied to a user behavior analysis system for a live platform, where the user behavior analysis system for a live platform includes a plurality of live edge servers, a cloud server, a plurality of play edge servers, and a plurality of play terminals, and the method includes:
the cloud server acquires historical live broadcasting behavior data of a live broadcasting room and historical live broadcasting room data of the live broadcasting room from the plurality of live broadcasting edge servers according to preset rules, wherein the historical live broadcasting behavior data comprise anchor action data, anchor dressing data, anchor voice data and virtual dressing data, and the historical live broadcasting room data comprise historical online people, historical environment data, historical background sound data and historical advertisement putting data;
the cloud server correspondingly acquires historical interaction behavior data of audiences in the live broadcasting room from the plurality of play edge servers, wherein the historical interaction behavior data comprise expression data, gesture data, bullet screen data, virtual gift data, praise data, advertisement clicking data, shopping cart data and commodity purchasing data;
Based on a time sequence, establishing an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data;
generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data;
and generating a standard live behavior portrait according to the association relation and the standard shopping portrait.
It may be understood that in this embodiment, the live edge server is disposed at a side closer to the live camera system, and is configured to perform preliminary processing on data transmitted by the live camera system, which may be an internet of things server; the cloud server is used for comprehensively managing the live broadcast edge server and the play edge server, and carrying out deep processing and universality processing on data; the playing edge server is arranged on the side closer to the playing terminal and is used for carrying out adaptability processing on data sent to the playing terminal or sent by the playing terminal; the playing terminal is used for users/spectators to watch live video and participate in live interaction through the live client.
It should be noted that, generating invalid interactive behavior portraits, standard interactive behavior portraits and standard shopping behavior portraits according to the historical interactive behavior data is specifically:
Inputting the historical interaction behavior data into a trained behavior classification model to obtain invalid interaction behavior data, standard interaction behavior data and standard shopping behavior data;
respectively carrying out feature processing on the invalid interaction behavior data, the standard interaction behavior data and the standard shopping behavior data, and generating N invalid interaction behavior feature data sets, N standard interaction behavior feature data sets and N standard shopping behavior feature data sets based on N preset different feature dimensions;
and constructing invalid interactive behavior portraits, standard interactive behavior portraits and standard shopping behavior portraits according to the N invalid interactive behavior feature data sets, the N standard interactive behavior feature data sets and the N standard shopping behavior feature data sets.
The following will exemplify only the construction flow of the invalid interactive behavior portrayal, and the construction of the standard interactive behavior portrayal and the standard shopping behavior portrayal are the same.
The construction flow of the invalid interactive behavior portrait is as follows:
generating an invalid interaction behavior feature model by utilizing the N invalid interaction behavior feature data sets;
performing data fusion after performing standardized processing on the N invalid interaction behavior feature data sets to obtain first feature data;
Processing the first characteristic data by using the invalid interaction behavior characteristic model to obtain evaluation data based on the preset N different characteristic dimensions;
constructing the invalid interactive behavior portrait by using the evaluation data;
wherein N is a positive integer.
In the embodiment of the invention, the cloud server acquires the historical live broadcast behavior data of a live broadcast room and the historical live broadcast room data of the live broadcast room from the plurality of live broadcast edge servers according to preset rules (such as a designated area range, a designated time period, a designated main broadcasting style, a designated live broadcast content type and the like), correspondingly acquires the historical interaction behavior data of a spectator of the live broadcast room from the plurality of play edge servers, and establishes an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data based on a time sequence; generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data; and generating a standard live behavior portrait according to the association relation and the standard shopping portrait. By the scheme provided by the embodiment of the invention, the standard live broadcast guide can be obtained based on the interaction behavior of the live broadcast room, and the live broadcast efficiency can be effectively improved in time.
In some possible embodiments of the invention, the method further comprises:
the cloud server selects a first direct broadcast edge server from the plurality of direct broadcast edge servers;
the cloud server acquires first direct broadcast video data of a first main broadcast between first direct broadcast and first live broadcast room data of the first live broadcast room from the first direct broadcast edge server;
judging whether the live behavior of the first host and/or the arrangement of the first live broadcasting room meets the current live broadcasting requirement according to the standard live broadcasting behavior portrait, the first live broadcasting room data and the first live broadcasting video data;
if yes, integrating the first direct broadcast video data and the first live broadcasting room data into first direct broadcast data, sending the first direct broadcast data to a corresponding first playing edge server in the plurality of playing edge servers, and forwarding the first direct broadcast video data and the first direct broadcast data to the plurality of playing terminals or the first playing terminals in the plurality of playing terminals by the first playing edge server;
if the video data does not accord with the standard live broadcast behavior portraits, outputting an improvement suggestion, or modifying the first live broadcast video data and the first live broadcast room data according to the standard live broadcast behavior portraits, integrating to obtain second live broadcast data, sending the second live broadcast data to the corresponding first playing edge server in the playing edge servers, and forwarding the second live broadcast data to the playing terminals or the first playing terminals in the playing terminals by the first playing edge server.
It may be appreciated that, in order to make the live action of the host and the decoration/rendering effect of the live room (such as the aspects of environment and background music) better conform to the live content, the commodity, the viewer preference, etc., in this embodiment, it is determined whether the current live action/live room arrangement conforms to the current live demand, if not, an improvement suggestion (such as an improvement suggestion on the aspects of the action, the mood, the dressing, the virtual video rendering of the live room, the background music, etc. of the first host) is output, or, after the first live action representation is modified, the first live video data and the first live room data are intelligently and automatically modified through an algorithm preset by a cloud server, so as to integrate to obtain second live data, and the second live data is sent to the corresponding first play border server in the plurality of play border servers, and is forwarded to the plurality of play terminals or the first play terminal in the plurality of play terminals by the first play border server.
In some possible embodiments of the invention, the method further comprises:
the cloud server acquires first interaction behavior data of audience of the first live broadcasting room;
Determining invalid interaction audiences according to the invalid interaction behavior portraits and the first interaction behavior data, and taking invalid interaction corresponding measures for the interaction behaviors of the invalid interaction audiences;
determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking standard interaction corresponding measures for the interaction behaviors of the standard interaction audience;
and determining a shopping interaction audience by the standard shopping behavior portrait and the first interaction behavior data, and taking shopping interaction countermeasure for the interaction behavior of the shopping interaction audience.
It may be appreciated that, in order to improve the effectiveness of the interaction behavior of the live broadcasting room, in this embodiment, the cloud server determines, according to the invalid interaction behavior representation, the standard interaction behavior representation and the first interaction behavior data, an invalid interaction audience, a standard interaction audience and a shopping interaction audience, and respectively takes an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience, a standard interaction countermeasure for the interaction behavior of the standard interaction audience, and a shopping interaction countermeasure for the interaction behavior of the shopping interaction audience, so as to interact with different types of audience in a targeted manner, thereby improving interaction efficiency.
In some possible embodiments of the present invention, the step of determining an invalid interaction audience according to the invalid interaction portrait and the first interaction behavior data, and taking an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience includes:
the bullet screen data and comment data are proposed from the first interactive behavior data, and the first invalid bullet screen data and the first invalid comment data are determined according to the invalid interactive behavior portraits;
according to the relevance of the context, combining the first invalid barrage data and the first invalid comment data to determine second invalid barrage data and second invalid comment data;
determining corresponding bullet screen senders and comment outputters according to the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data, and determining the bullet screen senders and the comment outputters as the invalid interaction audience;
aiming at the interaction behaviors of the invalid interaction audience, optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data;
And pre-examining the follow-up interaction behavior of the invalid interaction audience, judging whether the follow-up interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience.
It can be understood that management of invalid interaction behaviors is enhanced, negative effects of malicious interaction behaviors are eliminated, in this embodiment, invalid interaction data in first interaction behavior data is determined according to the invalid interaction behavior portrait, and according to relevance of context, associated invalid interaction behavior data is extracted, and then invalid interaction spectators are determined. Optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data (such as shielding inequality words/images, automatically adding interpretation reply words and the like) aiming at the interaction behaviors of the invalid interaction audience; and pre-examining the subsequent interaction behavior of the invalid interaction audience, judging whether the subsequent interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience, namely limiting the operation of the invalid interaction audience on a live broadcast client.
In some possible embodiments of the present invention, the step of determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking standard interaction countermeasure for the interaction behavior of the standard interaction audience includes:
extracting gift virtual gift data, praise data and click advertisement data from the first interaction behavior data;
determining first standard barrage data, first standard comment data, first standard presentation virtual gift data, first standard approval data and first standard click advertisement data according to the standard interaction behavior portrait, the barrage data, the comment data, the presentation virtual gift data, the approval data and the click advertisement data;
according to the relevance of the context, combining the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data and the first standard click advertisement data to determine second standard barrage data, second standard comment data, second standard gifting virtual gift data, second standard praise data and second standard click advertisement data;
Determining the standard interactive audience according to the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data, the first standard click advertisement data, the second standard barrage data, the second standard comment data, the second standard gifting virtual gift data, the second standard praise data and the second standard click advertisement data;
acquiring character feature data of the standard interactive audience, and acquiring character portrait data according to the character feature data;
and according to the character portrait data, the interaction behavior of the standard interaction audience is interacted, so that commodity purchase of the standard interaction audience is promoted.
It can be understood that, in order to promote the transformation of the interaction behavior in the live broadcasting room and improve the positive effect of the live broadcasting, the audience (i.e. the standard interaction audience) watching the live broadcasting in the live broadcasting room and having no negative emotion but not strong purchase intention is subjected to the focused and targeted interaction, in this embodiment, the standard interaction behavior data is selected from the first interaction behavior data according to the standard interaction behavior portrait, and after the standard interaction audience is further determined, the character feature data of the standard interaction audience is obtained, and the character portrait data is obtained according to the character feature data; and according to the figure data, the interaction behavior of the standard interaction audience is interacted (such as pushing commodity functions which can feel interest, pushing commodity combinations which can feel interest and benefit and meet the requirements according to the figure characteristic key/introduction, and the like) so as to promote the standard interaction audience to purchase commodities.
It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, such as the above-described division of units, merely a division of logic functions, and there may be additional manners of dividing in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, or may be in electrical or other forms.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units described above, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the above-mentioned method of the various embodiments of the present application. And the aforementioned memory includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps in the various methods of the above embodiments may be implemented by a program that instructs associated hardware, and the program may be stored in a computer readable memory, which may include: flash disk, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), magnetic disk or optical disk.
The foregoing has outlined rather broadly the more detailed description of embodiments of the present application, wherein specific examples are provided herein to illustrate the principles and embodiments of the present application, the above examples being provided solely to assist in the understanding of the methods of the present application and the core ideas thereof; meanwhile, as those skilled in the art will have modifications in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Although the present invention is disclosed above, the present invention is not limited thereto. Variations and modifications, including combinations of the different functions and implementation steps, as well as embodiments of the software and hardware, may be readily apparent to those skilled in the art without departing from the spirit and scope of the invention.

Claims (10)

1. A user behavior analysis system for a live platform, comprising: the system comprises a plurality of live broadcast edge servers, a cloud server, a plurality of play edge servers and a plurality of play terminals; wherein, the liquid crystal display device comprises a liquid crystal display device,
the cloud server is configured to:
acquiring historical live broadcasting behavior data of a live broadcasting room and historical live broadcasting room data of the live broadcasting room from the plurality of live broadcasting edge servers according to preset rules, wherein the historical live broadcasting behavior data comprise anchor action data, anchor dressing data, anchor voice data and virtual dressing data, and the historical live broadcasting room data comprise historical online people, historical environment data, historical background sound data and historical advertisement putting data;
correspondingly acquiring historical interaction behavior data of audiences in the live broadcasting room from the plurality of play edge servers, wherein the historical interaction behavior data comprise expression data, gesture data, bullet screen data, virtual gift data, praying data, click advertisement data, shopping cart data and commodity purchasing data;
based on a time sequence, establishing an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data;
Generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data;
and generating a standard live behavior portrait according to the association relation and the standard shopping portrait.
2. The user behavior analysis system for a live platform of claim 1, wherein the cloud server is further configured to:
the cloud server selects a first direct broadcast edge server from the plurality of direct broadcast edge servers;
the cloud server acquires first direct broadcast video data of a first main broadcast between first direct broadcast and first live broadcast room data of the first live broadcast room from the first direct broadcast edge server;
judging whether the live behavior of the first host and/or the arrangement of the first live broadcasting room meets the current live broadcasting requirement according to the standard live broadcasting behavior portrait, the first live broadcasting room data and the first live broadcasting video data;
if yes, integrating the first direct broadcast video data and the first live broadcasting room data into first direct broadcast data, sending the first direct broadcast data to a corresponding first playing edge server in the plurality of playing edge servers, and forwarding the first direct broadcast video data and the first direct broadcast data to the plurality of playing terminals or the first playing terminals in the plurality of playing terminals by the first playing edge server;
If the video data does not accord with the standard live broadcast behavior portraits, outputting an improvement suggestion, or modifying the first live broadcast video data and the first live broadcast room data according to the standard live broadcast behavior portraits, integrating to obtain second live broadcast data, sending the second live broadcast data to the corresponding first playing edge server in the playing edge servers, and forwarding the second live broadcast data to the playing terminals or the first playing terminals in the playing terminals by the first playing edge server.
3. The user behavior analysis system for a live platform of claim 2, wherein the cloud server is further configured to:
acquiring first interaction behavior data of audience of the first living broadcast room;
determining invalid interaction audiences according to the invalid interaction behavior portraits and the first interaction behavior data, and taking invalid interaction corresponding measures for the interaction behaviors of the invalid interaction audiences;
determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking standard interaction corresponding measures for the interaction behaviors of the standard interaction audience;
and determining a shopping interaction audience by the standard shopping behavior portrait and the first interaction behavior data, and taking shopping interaction countermeasure for the interaction behavior of the shopping interaction audience.
4. A user behavior analysis system for a live platform according to claim 3, wherein in the step of determining an invalid interaction audience from the invalid interaction portraits and the first interaction behavior data and taking an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience, the cloud server is specifically configured to:
the bullet screen data and comment data are proposed from the first interactive behavior data, and the first invalid bullet screen data and the first invalid comment data are determined according to the invalid interactive behavior portraits;
according to the relevance of the context, combining the first invalid barrage data and the first invalid comment data to determine second invalid barrage data and second invalid comment data;
determining corresponding bullet screen senders and comment outputters according to the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data, and determining the bullet screen senders and the comment outputters as the invalid interaction audience;
aiming at the interaction behaviors of the invalid interaction audience, optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data;
And pre-examining the follow-up interaction behavior of the invalid interaction audience, judging whether the follow-up interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience.
5. The user behavior analysis system for a live platform of claims 1-4, wherein in the step of determining a standard interaction audience from the standard interaction behavior representation and the first interaction behavior data and taking standard interaction countermeasures for the interaction behavior of the standard interaction audience, the cloud server is specifically configured to:
extracting gift virtual gift data, praise data and click advertisement data from the first interaction behavior data;
determining first standard barrage data, first standard comment data, first standard presentation virtual gift data, first standard approval data and first standard click advertisement data according to the standard interaction behavior portrait, the barrage data, the comment data, the presentation virtual gift data, the approval data and the click advertisement data;
According to the relevance of the context, combining the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data and the first standard click advertisement data to determine second standard barrage data, second standard comment data, second standard gifting virtual gift data, second standard praise data and second standard click advertisement data;
determining the standard interactive audience according to the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data, the first standard click advertisement data, the second standard barrage data, the second standard comment data, the second standard gifting virtual gift data, the second standard praise data and the second standard click advertisement data;
acquiring character feature data of the standard interactive audience, and acquiring character portrait data according to the character feature data;
and according to the character portrait data, the interaction behavior of the standard interaction audience is interacted, so that commodity purchase of the standard interaction audience is promoted.
6. A user behavior analysis method for a live platform, applied to the user behavior analysis system for a live platform according to claims 1-5, the user behavior analysis system for a live platform including a plurality of live edge servers, a cloud server, a plurality of play edge servers, and a plurality of play terminals, the method comprising:
the cloud server acquires historical live broadcasting behavior data of a live broadcasting room and historical live broadcasting room data of the live broadcasting room from the plurality of live broadcasting edge servers according to preset rules, wherein the historical live broadcasting behavior data comprise anchor action data, anchor dressing data, anchor voice data and virtual dressing data, and the historical live broadcasting room data comprise historical online people, historical environment data, historical background sound data and historical advertisement putting data;
the cloud server correspondingly acquires historical interaction behavior data of audiences in the live broadcasting room from the plurality of play edge servers, wherein the historical interaction behavior data comprise expression data, gesture data, bullet screen data, virtual gift data, praise data, advertisement clicking data, shopping cart data and commodity purchasing data;
Based on a time sequence, establishing an association relationship among the historical live broadcast behavior data, the historical live broadcast room data and the historical interaction behavior data;
generating an invalid interaction behavior portrait, a standard interaction behavior portrait and a standard shopping behavior portrait according to the historical interaction behavior data;
and generating a standard live behavior portrait according to the association relation and the standard shopping portrait.
7. The method of user behavior analysis for a live platform of claim 6, further comprising:
the cloud server selects a first direct broadcast edge server from the plurality of direct broadcast edge servers;
the cloud server acquires first direct broadcast video data of a first main broadcast between first direct broadcast and first live broadcast room data of the first live broadcast room from the first direct broadcast edge server;
judging whether the live behavior of the first host and/or the arrangement of the first live broadcasting room meets the current live broadcasting requirement according to the standard live broadcasting behavior portrait, the first live broadcasting room data and the first live broadcasting video data;
if yes, integrating the first direct broadcast video data and the first live broadcasting room data into first direct broadcast data, sending the first direct broadcast data to a corresponding first playing edge server in the plurality of playing edge servers, and forwarding the first direct broadcast video data and the first direct broadcast data to the plurality of playing terminals or the first playing terminals in the plurality of playing terminals by the first playing edge server;
If the video data does not accord with the standard live broadcast behavior portraits, outputting an improvement suggestion, or modifying the first live broadcast video data and the first live broadcast room data according to the standard live broadcast behavior portraits, integrating to obtain second live broadcast data, sending the second live broadcast data to the corresponding first playing edge server in the playing edge servers, and forwarding the second live broadcast data to the playing terminals or the first playing terminals in the playing terminals by the first playing edge server.
8. The method of user behavior analysis for a live platform of claim 7, further comprising:
the cloud server acquires first interaction behavior data of audience of the first live broadcasting room;
determining invalid interaction audiences according to the invalid interaction behavior portraits and the first interaction behavior data, and taking invalid interaction corresponding measures for the interaction behaviors of the invalid interaction audiences;
determining a standard interaction audience according to the standard interaction behavior portrait and the first interaction behavior data, and taking standard interaction corresponding measures for the interaction behaviors of the standard interaction audience;
and determining a shopping interaction audience by the standard shopping behavior portrait and the first interaction behavior data, and taking shopping interaction countermeasure for the interaction behavior of the shopping interaction audience.
9. The method for analyzing user behavior of a live platform according to claim 8, wherein the step of determining an invalid interaction audience from the invalid interaction portraits and the first interaction behavior data and taking an invalid interaction countermeasure for the interaction behavior of the invalid interaction audience comprises:
the bullet screen data and comment data are proposed from the first interactive behavior data, and the first invalid bullet screen data and the first invalid comment data are determined according to the invalid interactive behavior portraits;
according to the relevance of the context, combining the first invalid barrage data and the first invalid comment data to determine second invalid barrage data and second invalid comment data;
determining corresponding bullet screen senders and comment outputters according to the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data, and determining the bullet screen senders and the comment outputters as the invalid interaction audience;
aiming at the interaction behaviors of the invalid interaction audience, optimizing the first invalid bullet screen data, the first invalid comment data, the second invalid bullet screen data and the second invalid comment data;
And pre-examining the follow-up interaction behavior of the invalid interaction audience, judging whether the follow-up interaction behavior is invalid or not according to the invalid interaction behavior portrait, if so, sending the interaction data to the first direct broadcast edge server, and limiting the interaction function of the invalid interaction audience.
10. A user behavior analysis method for a live platform according to claims 6-9, wherein the step of determining a standard interactive audience from the standard interactive behavior representation and the first interactive behavior data and taking standard interactive countermeasures for the interactive behavior of the standard interactive audience comprises:
extracting gift virtual gift data, praise data and click advertisement data from the first interaction behavior data;
determining first standard barrage data, first standard comment data, first standard presentation virtual gift data, first standard approval data and first standard click advertisement data according to the standard interaction behavior portrait, the barrage data, the comment data, the presentation virtual gift data, the approval data and the click advertisement data;
according to the relevance of the context, combining the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data and the first standard click advertisement data to determine second standard barrage data, second standard comment data, second standard gifting virtual gift data, second standard praise data and second standard click advertisement data;
Determining the standard interactive audience according to the first standard barrage data, the first standard comment data, the first standard gifting virtual gift data, the first standard praise data, the first standard click advertisement data, the second standard barrage data, the second standard comment data, the second standard gifting virtual gift data, the second standard praise data and the second standard click advertisement data;
acquiring character feature data of the standard interactive audience, and acquiring character portrait data according to the character feature data;
and according to the character portrait data, the interaction behavior of the standard interaction audience is interacted, so that commodity purchase of the standard interaction audience is promoted.
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