CN113301376B - Live broadcast interaction method and system based on virtual reality technology - Google Patents
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- 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
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/431—Generation of visual interfaces for content selection or interaction; Content or additional data rendering
- H—ELECTRICITY
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- 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
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- 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
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- H04N21/488—Data services, e.g. news ticker
- H04N21/4884—Data services, e.g. news ticker for displaying subtitles
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Abstract
Translated fromChinese
Description
Translated fromChinese技术领域technical field
本发明涉及人工智能领域，尤其涉及一种基于虚拟现实技术的直播交互方式及系统。The present invention relates to the field of artificial intelligence, in particular to a live interactive method and system based on virtual reality technology.
背景技术Background technique
近年来随着互联网技术的高速发展，衍生出一批便捷、有吸引力的网络娱乐方式。网络直播作为一种新兴产业，吸取和延续了互联网的优势，利用视讯方式进行网上现场直播，可以将产品展示、相关会议、背景介绍、方案测评、网上调查、对话访谈、在线培训等内容现场发布到互联网上，利用互联网的直观、快速，表现形式好、内容丰富、交互性强、地域不受限制、受众可划分等特点，加强活动现场的推广效果。现场直播完成后，还可以随时为读者继续提供重播、点播，有效延长了直播的时间和空间，发挥直播内容的最大价值。In recent years, with the rapid development of Internet technology, a number of convenient and attractive online entertainment methods have been derived. As an emerging industry, webcasting has absorbed and continued the advantages of the Internet. It uses video to broadcast live online, and can release product demonstrations, related meetings, background introductions, program evaluations, online surveys, dialogues and interviews, online training, etc. on the spot. Going to the Internet, using the characteristics of the Internet such as intuition, speed, good form, rich content, strong interactivity, unlimited regions, and divisible audiences, etc., to strengthen the promotion effect of the event site. After the live broadcast is completed, readers can continue to provide replays and on-demand broadcasts at any time, which effectively extends the time and space of the live broadcast and maximizes the value of the live broadcast content.
本申请发明人在实现本申请实施例中发明技术方案的过程中，发现上述技术至少存在如下技术问题：In the process of realizing the technical solution of the invention in the embodiment of the present application, the inventor of the present application found that the above-mentioned technology has at least the following technical problems:
网络直播的形式限定了其“一对多”的特征，即进行直播展示的一方人数有限，多数情况下为一名主播或一支主播团队，而观看直播的观众人数不会受到限制。现有技术中主播与观众之间往往通过观众发出的弹幕信息进行交流互动，而当观众基数巨大时，弹幕数量剧增，主播一方难免会忽略部分弹幕信息，而导致部分观众的观看留言无法得到主播一方的反馈，会间接影响观众的观感，降低观众黏性，以至于影响直播效果。The form of online live broadcasting limits its "one-to-many" feature, that is, the number of parties performing live broadcasting is limited, in most cases it is an anchor or a team of anchors, and the number of viewers watching the live broadcast is not limited. In the existing technology, the anchor and the audience often communicate and interact through the barrage information sent by the audience. When the audience base is huge, the number of barrages increases sharply, and the anchor will inevitably ignore some of the barrage information, which will cause some viewers to watch. Messages cannot get feedback from the anchor side, which will indirectly affect the audience's perception, reduce audience stickiness, and even affect the live broadcast effect.
发明内容Contents of the invention
本申请实施例通过提供一种基于虚拟现实技术的直播交互方式及系统，解决了现有技术中直播观众数量庞大时主播方无法全面且及时对弹幕信息进行反馈导致观众体验不佳的技术问题，通过构建自动回复特征库并对直播弹幕进行智能回复，达到了及时反馈弹幕信息的技术目的，实现了提高直播观感和观众满意度的技术效果，进一步提高了观众黏性，保障了网络直播行业的良好发展。The embodiment of the present application provides a live broadcast interaction method and system based on virtual reality technology, which solves the technical problem in the prior art that the host cannot provide comprehensive and timely feedback on the barrage information when the number of live viewers is large, resulting in poor audience experience. , by building an automatic reply feature library and intelligently replying to live barrage, the technical purpose of timely feedback of barrage information is achieved, the technical effect of improving live broadcast perception and audience satisfaction is achieved, audience stickiness is further improved, and network security is ensured. The good development of the live broadcast industry.
鉴于上述问题，本申请实施例提供一种基于虚拟现实技术的直播交互方式及系统。In view of the above problems, the embodiments of the present application provide a live broadcast interaction method and system based on virtual reality technology.
第一方面，本申请提供了一种基于虚拟现实技术的直播交互方式，其中，所述方式应用于一信息中转平台，所述方式包括：根据信息处理平台收集第一直播间内的弹幕信息集合；根据大数据获得多个弹幕分类特征；根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；根据所述多个信息熵，构建弹幕分类决策树；根据所述弹幕分类决策树，获得第一分类结果；构建自动回复特征库；判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；如果所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复。In the first aspect, the present application provides a live broadcast interaction method based on virtual reality technology, wherein the method is applied to an information transfer platform, and the method includes: collecting barrage information in the first live broadcast room according to the information processing platform Set; obtain a plurality of barrage classification features according to the big data; classify the barrage information collection according to the plurality of barrage classification features, and perform information theory coding operations to obtain a plurality of information entropies; according to the plurality of information Entropy, constructing a barrage classification decision tree; according to the barrage classification decision tree, obtaining the first classification result; constructing an automatic reply feature library; judging whether there is a barrage belonging to the automatic reply feature library in the first classification result Information; if there is bullet chatting information belonging to the automatic reply feature database in the first classification result, automatically replying to the bullet chat information belonging to the automatic reply feature database according to the automatic reply feature database.
另一方面，本申请还提供了一种基于虚拟现实技术的直播交互系统，其中，所述系统包括：第一收集单元，所述第一收集单元用于根据信息处理平台收集第一直播间内的弹幕信息集合；第一获得单元，所述第一获得单元用于根据大数据获得多个弹幕分类特征；第二获得单元，所述第二获得单元用于根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；第一构建单元，所述第一构建单元用于根据所述多个信息熵，构建弹幕分类决策树；第三获得单元，所述第三获得单元用于根据所述弹幕分类决策树，获得第一分类结果；第二构建单元，所述第二构建单元用于构建自动回复特征库；第一判断单元，所述第一判断单元用于判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；第一执行单元，所述第一执行单元用于当所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复。On the other hand, the present application also provides a live broadcast interaction system based on virtual reality technology, wherein the system includes: a first collection unit, which is used to collect information in the first live broadcast room according to the information processing platform The bullet chatting information set; the first obtaining unit, the first obtaining unit is used to obtain a plurality of bullet chatting classification features according to the big data; the second obtaining unit, the second obtaining unit is used to obtain according to the multiple bullet chatting features The classification feature classifies the bullet chat information collection, and performs information theory coding operations to obtain multiple information entropies; the first construction unit is used to construct bullet chat classification decisions based on the multiple information entropies Tree; the third obtaining unit, the third obtaining unit is used to obtain the first classification result according to the barrage classification decision tree; the second construction unit, the second construction unit is used to construct the automatic reply feature library; A judging unit, the first judging unit is used to judge whether there is barrage information belonging to the automatic reply feature library in the first classification result; a first execution unit, the first execution unit is used when the The bullet chatting information belonging to the automatic reply feature database exists in the first classification result, and the bullet chatting information belonging to the automatic reply feature database is automatically replied according to the automatic reply feature database.
另一方面，本申请实施例还提供了一种基于虚拟现实技术的直播交互系统，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，所述处理器执行所述程序时实现上述第一方面所述方法的步骤。On the other hand, the embodiment of the present application also provides a live interactive system based on virtual reality technology, including a memory, a processor, and a computer program stored in the memory and operable on the processor, wherein the processor executes The program is the steps to implement the method described in the first aspect above.
本申请实施例中提供的一个或多个技术方案，至少具有如下技术效果或优点：One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:
本申请实施例提供了一种基于虚拟现实技术的直播交互方式，通过根据信息处理平台收集第一直播间内的弹幕信息集合；根据大数据获得多个弹幕分类特征；根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；根据所述多个信息熵，构建弹幕分类决策树；根据所述弹幕分类决策树，获得第一分类结果；构建自动回复特征库；判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；如果所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复，解决了现有技术中直播观众数量庞大时主播方无法全面且及时对弹幕信息进行反馈导致观众体验不佳的技术问题，通过构建自动回复特征库并对直播弹幕进行智能回复，达到了及时反馈弹幕信息的技术目的，实现了提高直播观感和观众满意度的技术效果，进一步提高了观众黏性，保障了网络直播行业的良好发展。The embodiment of the present application provides a live broadcast interaction method based on virtual reality technology, by collecting the bullet chat information set in the first live broadcast room according to the information processing platform; obtaining multiple bullet chat classification features according to the big data; according to the multiple The barrage classification feature classifies the barrage information collection, and performs information theory coding operations to obtain a plurality of information entropies; according to the plurality of information entropies, construct a barrage classification decision tree; according to the barrage classification decision tree, Obtaining the first classification result; building an automatic reply feature library; judging whether there is barrage information belonging to the automatic reply feature library in the first classification result; if there is a barrage information belonging to the automatic reply feature library in the first classification result According to the automatic reply feature library, the bullet chat information belonging to the automatic reply feature library is automatically replied, which solves the problem that the anchor cannot comprehensively and timely check the bullet chat information when the number of live viewers is huge in the prior art. Feedback on technical issues that lead to poor audience experience. By building an automatic reply feature library and intelligently replying to live barrage, the technical purpose of timely feedback of barrage information has been achieved, and the technical effect of improving live broadcast perception and audience satisfaction has been further achieved. It improves audience stickiness and ensures the sound development of the webcast industry.
上述说明是本申请技术方案的概述，为了能够更清楚了解本申请的技术手段，而可依照说明书的内容予以实施，并且为了让本申请的上述和其他目的、特征和优点能够更明显易懂，以下特举本申请的具体实施方式。The above description is an overview of the technical solution of the present application. In order to understand the technical means of the present application more clearly, it can be implemented according to the contents of the description, and in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, Specific embodiments of the present application are enumerated below.
附图说明Description of drawings
图1为本申请实施例一种基于虚拟现实技术的直播交互方式的流程示意图；FIG. 1 is a schematic flow diagram of a live interactive mode based on virtual reality technology according to an embodiment of the present application;
图2为本申请实施例一种基于虚拟现实技术的直播交互系统的结构示意图；FIG. 2 is a schematic structural diagram of a live interactive system based on virtual reality technology according to an embodiment of the present application;
图3为本申请实施例示例性电子设备的结构示意图。Fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
附图标记说明：第一收集单元11，第一获得单元，第二获得单元13，第一构建单元14，第三获得单元15，第二构建单元16，第一判断单元17，第一执行单元18，总线300，接收器301，处理器302，发送器303，存储器304，总线接口305。Explanation of reference numerals:
具体实施方式Detailed ways
本申请实施例通过提供一种基于虚拟现实技术的直播交互方式及系统，解决了现有技术中直播观众数量庞大时主播方无法全面且及时对弹幕信息进行反馈导致观众体验不佳的技术问题，通过构建自动回复特征库并对直播弹幕进行智能回复，达到了及时反馈弹幕信息的技术目的，实现了提高直播观感和观众满意度的技术效果，进一步提高了观众黏性，保障了网络直播行业的良好发展。The embodiment of the present application provides a live broadcast interaction method and system based on virtual reality technology, which solves the technical problem in the prior art that the host cannot provide comprehensive and timely feedback on the barrage information when the number of live viewers is large, resulting in poor audience experience. , by building an automatic reply feature library and intelligently replying to live barrage, the technical purpose of timely feedback of barrage information is achieved, the technical effect of improving live broadcast perception and audience satisfaction is achieved, audience stickiness is further improved, and network security is ensured. The good development of the live broadcast industry.
下面，将参考附图详细地描述本申请的示例实施例，显然，所描述的实施例仅是本申请的一部分实施例，而不是本申请的全部实施例，应理解，本申请不受这里描述的示例实施例的限制。Below, the exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Limitations of the example embodiment.
申请概述Application overview
近年来随着互联网技术的高速发展，衍生出一批便捷、有吸引力的网络娱乐方式。网络直播作为一种新兴产业，吸取和延续了互联网的优势，利用视讯方式进行网上现场直播，可以将产品展示、相关会议、背景介绍、方案测评、网上调查、对话访谈、在线培训等内容现场发布到互联网上，利用互联网的直观、快速，表现形式好、内容丰富、交互性强、地域不受限制、受众可划分等特点，加强活动现场的推广效果。现场直播完成后，还可以随时为读者继续提供重播、点播，有效延长了直播的时间和空间，发挥直播内容的最大价值。网络直播的形式限定了其“一对多”的特征，即进行直播展示的一方人数有限，多数情况下为一名主播或一支主播团队，而观看直播的观众人数不会受到限制。现有技术中主播与观众之间往往通过观众发出的弹幕信息进行交流互动，而当观众基数巨大时，弹幕数量剧增，主播一方难免会忽略部分弹幕信息，而导致部分观众的观看留言无法得到主播一方的反馈，会间接影响观众的观感，降低观众黏性，以至于影响直播效果。In recent years, with the rapid development of Internet technology, a number of convenient and attractive online entertainment methods have been derived. As an emerging industry, webcasting has absorbed and continued the advantages of the Internet. It uses video to broadcast live online, and can release product demonstrations, related meetings, background introductions, program evaluations, online surveys, dialogues and interviews, online training, etc. on the spot. Going to the Internet, using the characteristics of the Internet such as intuition, speed, good form, rich content, strong interactivity, unlimited regions, and divisible audiences, etc., to strengthen the promotion effect of the event site. After the live broadcast is completed, readers can continue to provide replays and on-demand broadcasts at any time, which effectively extends the time and space of the live broadcast and maximizes the value of the live broadcast content. The form of online live broadcasting limits its "one-to-many" feature, that is, the number of parties performing live broadcasting is limited, in most cases it is an anchor or a team of anchors, and the number of viewers watching the live broadcast is not limited. In the existing technology, the anchor and the audience often communicate and interact through the barrage information sent by the audience. When the audience base is huge, the number of barrages increases sharply, and the anchor will inevitably ignore some of the barrage information, which will cause some viewers to watch. Messages cannot get feedback from the anchor side, which will indirectly affect the audience's perception, reduce audience stickiness, and even affect the live broadcast effect.
针对上述技术问题，本申请提供的技术方案总体思路如下：In view of the above technical problems, the general idea of the technical solution provided by this application is as follows:
本申请提供了一种基于虚拟现实技术的直播交互方式及系统，其中，所述方式应用于一信息中转平台，所述方式包括：根据信息处理平台收集第一直播间内的弹幕信息集合；根据大数据获得多个弹幕分类特征；根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；根据所述多个信息熵，构建弹幕分类决策树；根据所述弹幕分类决策树，获得第一分类结果；构建自动回复特征库；判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；如果所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复。The present application provides a live broadcast interaction method and system based on virtual reality technology, wherein the method is applied to an information transfer platform, and the method includes: collecting the barrage information collection in the first live broadcast room according to the information processing platform; Obtain a plurality of barrage classification features according to the big data; classify the barrage information set according to the plurality of barrage classification features, and perform information theory coding operations to obtain a plurality of information entropies; according to the plurality of information entropies, Build a barrage classification decision tree; obtain the first classification result according to the barrage classification decision tree; build an automatic reply feature library; judge whether there is barrage information belonging to the automatic reply feature library in the first classification result; If there is bullet chat information belonging to the automatic reply feature library in the first classification result, automatically reply to the bullet chat information belonging to the automatic reply feature database according to the automatic reply feature database.
在介绍了本申请基本原理后，下面将结合说明书附图来具体介绍本申请的各种非限制性的实施方式。After introducing the basic principles of the present application, various non-limiting implementations of the present application will be specifically introduced below in conjunction with the accompanying drawings.
实施例一Embodiment one
如图1所示，本申请实施例提供了一种基于虚拟现实技术的直播交互方式，其中，所述方式包括：As shown in Figure 1, the embodiment of the present application provides a live interactive method based on virtual reality technology, wherein the method includes:
步骤S100：根据信息处理平台收集第一直播间内的弹幕信息集合；Step S100: collect the barrage information set in the first live broadcast room according to the information processing platform;
具体而言，弹幕指直接显现在视频上的评论，可以滚动、停留甚至更多动作特效方式出现在视频上，是观看视频的人发送的简短评论。在网络直播过程中，弹幕具有实时性的特点，任何人都可以通过弹幕消息发表自己的看法，主播也可以通过直播弹幕为观众答疑解惑，拉近与观众之间的距离。所述第一直播间内的弹幕信息集合即本场次直播中观众发出的所有弹幕消息，包含观众对直播的评价、对主播的建议以及直播过程中的疑问等。弹幕信息集合不仅限于与直播相关的言论，例如观众的无厘头发言以及网络流行语的使用均包含在内。通过获得所述弹幕信息集合，能够为实现主播与观众的全面互动奠定基础。Specifically, barrage refers to the comments that appear directly on the video, which can be scrolled, paused, or even appear on the video with more action special effects. It is a short comment sent by the person watching the video. In the process of webcasting, the barrage is real-time. Anyone can express their opinions through the barrage message. The host can also answer questions for the audience through the live barrage, shortening the distance between the audience and the audience. The barrage information set in the first live broadcast room refers to all the barrage messages sent by the audience in this live broadcast, including the audience's evaluation of the live broadcast, suggestions for the anchor, and questions during the live broadcast. The collection of barrage information is not limited to remarks related to live broadcasts, such as nonsensical speeches by the audience and the use of Internet buzzwords. By obtaining the barrage information set, a foundation can be laid for realizing the comprehensive interaction between the anchor and the audience.
步骤S200：根据大数据获得多个弹幕分类特征；Step S200: Obtain multiple barrage classification features according to big data;
具体而言，所述弹幕分类特征是对直播弹幕进行类别划分的一种参考量，例如，可以就弹幕信息与直播内容是否相关将弹幕进行划分，在“弹幕信息与直播内容相关”这个大纲下，还可以就弹幕信息的指向性对其进行细分。通过获得的多个弹幕分类特征，可将弹幕信息分为不同的类别，根据不同类别弹幕信息对其进行集中回复，可以提高回复效率，提高消息回复的全面性。Specifically, the bullet chat classification feature is a reference for classifying live bullet chat. For example, bullet chat information can be divided according to whether bullet chat information is related to live content. Under the outline of "related", the barrage information can also be subdivided in terms of its directionality. Through the obtained multiple barrage classification features, the barrage information can be divided into different categories, and the centralized reply can be made according to different types of barrage information, which can improve the efficiency of reply and the comprehensiveness of message reply.
步骤S300：根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；Step S300: Classify the bullet chatting information set according to the multiple bullet chatting classification features, and perform information theory coding operation to obtain multiple information entropies;
步骤S400：根据所述多个信息熵，构建弹幕分类决策树；Step S400: Construct a barrage classification decision tree according to the plurality of information entropies;
具体而言，通过所述多个弹幕分类特征对所述弹幕信息集合进行分类，并应用统计学方法获得通信系统中信息传递和信息处理的共同规律，进行信息论编码运算，获得多个信息熵。信息熵即信息的量化度量的表达，用来描述信源的不确定度，一个数据集的熵越大，则说明该数据分类的“纯度”越高。通过获得多个信息熵，可就弹幕分类情况构建弹幕分类决策树。决策树是机器学习的常见算法，分为分类树和回归树，当对一个样本的分类进行预测时使用分类树。分类决策树即根据训练数据集构造一个类似树形的分类决策模型，然后用这个模型来辅助决策。使用信息增益作为划分数据集的依据。整个数据集的熵称作原始熵，数据集根据某个特征划分之后的熵为条件熵，信息增益＝原始熵-条件熵。用信息增益划分的具体做法是：计算每一类特征对应的信息增益，然后挑选信息增益最小的特征进行划分。通过构建弹幕分类决策树可以实现对弹幕信息的精准划分，便于精确回复。Specifically, classify the bullet chatting information set through the multiple bullet chatting classification features, and apply statistical methods to obtain the common law of information transmission and information processing in the communication system, perform information theory coding operations, and obtain multiple information entropy. Information entropy is the expression of the quantitative measure of information, which is used to describe the uncertainty of the information source. The greater the entropy of a data set, the higher the "purity" of the data classification. By obtaining multiple information entropies, a bullet chat classification decision tree can be constructed for the bullet chat classification. Decision tree is a common algorithm of machine learning. It is divided into classification tree and regression tree. When predicting the classification of a sample, the classification tree is used. The classification decision tree is to construct a tree-like classification decision model based on the training data set, and then use this model to assist decision-making. Use information gain as a basis for partitioning a dataset. The entropy of the entire data set is called the original entropy, and the entropy after the data set is divided according to a certain feature is the conditional entropy, and information gain = original entropy - conditional entropy. The specific method of dividing by information gain is: calculate the information gain corresponding to each type of feature, and then select the feature with the smallest information gain for division. By constructing a barrage classification decision tree, the precise division of barrage information can be realized, which is convenient for accurate reply.
步骤S500：根据所述弹幕分类决策树，获得第一分类结果；Step S500: Obtain a first classification result according to the bullet chat classification decision tree;
具体而言，所述第一分类结果根据弹幕分类决策树获得，是基于弹幕分类特征对弹幕信息集合进行合理划分的结果，基于大数据对弹幕信息集合做出的智能化分析结果。所述第一分类结果可以是对主播推销的产品进行分类，也可以是对直播的观感评价进行分类，通过获得第一分类结果，可以明确弹幕信息集合的类别情况，提高了弹幕信息的识别效率，进一步加快了弹幕信息回复速度。Specifically, the first classification result is obtained according to the bullet chat classification decision tree, which is the result of rationally dividing the bullet chat information set based on the bullet chat classification features, and the intelligent analysis result of the bullet chat information set based on big data . The first classification result can be to classify the products promoted by the anchor, or to classify the impression evaluation of the live broadcast. By obtaining the first classification result, the category situation of the bullet chat information collection can be clarified, and the accuracy of the bullet chat information can be improved. Recognition efficiency further speeds up the reply speed of barrage information.
步骤S600：构建自动回复特征库；Step S600: building an automatic reply feature library;
具体而言，所述自动回复特征库是对第一分类结果进行关键特征提取而构建的集合，自动回复特征库中的每一特征都有对应的自动回复语句，需要注意的是，由于汉语词汇中具有同义词，即不同词语表达的意思和效果是一样的，所以特征与自动回复语句并不是一一对应的关系，而是多个特征均可以对应一句自动回复语句。通过构建自动回复特征库，将第一分类结果与自动回复语句进行联系，有利于实现弹幕消息的精准回复。Specifically, the automatic reply feature library is a collection constructed by extracting key features from the first classification results. Each feature in the automatic reply feature library has a corresponding automatic reply sentence. It should be noted that due to the Chinese vocabulary There are synonyms in , that is, the meaning and effect expressed by different words are the same, so there is not a one-to-one correspondence between features and automatic reply sentences, but multiple features can correspond to one automatic reply sentence. By building an automatic reply feature library and linking the first classification result with the automatic reply sentence, it is beneficial to realize the accurate reply of the barrage message.
步骤S700：判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；Step S700: judging whether there is bullet chat information belonging to the automatic reply feature library in the first classification result;
步骤S800：如果所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复。Step S800: If there is bullet chat information belonging to the automatic reply feature library in the first classification result, automatically reply to the bullet chat information belonging to the automatic reply feature database according to the automatic reply feature database.
具体而言，在获得第一分类结果并完成构建自动回复特征库后，可以通过自动回复特征库判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息。如果所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，可以根据自动回复特征库直接对属于所述自动回复特征库的弹幕信息进行自动回复。通过特征识别和信息处理，达到了对弹幕信息智能化回复的目的，解决了现有技术中直播观众数量庞大时主播方无法全面且及时对弹幕信息进行反馈导致观众体验不佳的技术问题，达到了及时反馈弹幕信息的技术目的，实现了提高直播观感和观众满意度的技术效果，进一步提高了观众黏性，保障了网络直播行业的良好发展。Specifically, after the first classification result is obtained and the auto-reply feature database is built, it can be judged through the auto-reply feature database whether there is bullet chat information belonging to the auto-reply feature database in the first classification result. If there is bullet chatting information belonging to the automatic reply feature database in the first classification result, the bullet chat information belonging to the automatic reply feature database may be directly automatically replied according to the automatic reply feature database. Through feature recognition and information processing, the purpose of intelligently replying to the barrage information is achieved, and the technical problem in the prior art that the host cannot provide comprehensive and timely feedback on the barrage information when the number of live viewers is large in the prior art leads to poor audience experience. , achieved the technical purpose of timely feedback of barrage information, achieved the technical effect of improving the live broadcast perception and audience satisfaction, further improved audience stickiness, and ensured the sound development of the online live broadcast industry.
进一步地，本申请实施例步骤S400还包括：Further, step S400 in this embodiment of the present application also includes:
步骤S410：将所述多个信息熵输入数值大小比对模型，获得第一根节点特征信息；Step S410: Input the multiple information entropies into the numerical comparison model to obtain the characteristic information of the first root node;
步骤S420：基于递归算法，对所述第一根节点特征信息和所述弹幕信息集合进行计算，构建所述弹幕分类决策树。Step S420: Based on a recursive algorithm, calculate the feature information of the first root node and the bullet chat information set, and construct the bullet chat classification decision tree.
具体而言，所述数值大小比对模型用于对比多个信息熵的数值大小，信息熵越大，则说明该数据分类越合理。决策树中的树状结构就是各个元素之间具有分层关系的数据结构，常用一棵倒置的树来表示其逻辑关系，根节点就是树的最顶端的节点。通过递归算法，无限调用一个递归函数，对所述第一根节点特征信息和所述弹幕信息集合进行计算。每次调用改动一个关键变量，直到这个关键变量达到边界时递归完毕，通过结果值，构建所述弹幕分类决策树。基于递归算法，能够达到整体结构清晰，可读性强，且易用数学归纳法来证明算法的正确性的效果，因此它为设计算法、调试程序带来很大方便。Specifically, the numerical size comparison model is used to compare the numerical values of multiple information entropies, and the greater the information entropy, the more reasonable the data classification is. The tree structure in the decision tree is a data structure with a hierarchical relationship between elements. An inverted tree is often used to represent its logical relationship, and the root node is the top node of the tree. Through a recursive algorithm, a recursive function is infinitely called to calculate the feature information of the first root node and the barrage information set. Each call changes a key variable until the key variable reaches the boundary, and the recursion is completed, and the barrage classification decision tree is constructed through the result value. Based on the recursive algorithm, it can achieve clear overall structure, strong readability, and easy to use mathematical induction to prove the correctness of the algorithm, so it brings great convenience for designing algorithms and debugging programs.
进一步地，本申请实施例步骤S500还包括：Further, step S500 in this embodiment of the present application also includes:
步骤S510：获得第一弹幕信息，所述第一弹幕信息属于所述弹幕信息集合；Step S510: Obtain first bullet chat information, the first bullet chat information belongs to the bullet chat information set;
步骤S520：将所述第一弹幕信息输入所述弹幕分类决策树，对所述弹幕信息集合进行分类，获得所述第一分类结果。Step S520: Input the first bullet chat information into the bullet chat classification decision tree, classify the bullet chat information set, and obtain the first classification result.
具体而言，对弹幕进行分类的过程是按照信息条数逐一进行的，通过获得第一弹幕信息，并将所述第一弹幕信息输入所述弹幕分类决策树，对所述弹幕信息集合进行分类。所述第一弹幕信息属于所述弹幕信息集合，可以为任意时刻任意内容的弹幕信息，分类的结果代表所述第一弹幕信息的内容特征，将所有弹幕信息通过这种方式进行分类，可以得到与其对应的分类结果，根据该分类结果，可以匹配到合适的回复语句，便于进行智能回复。Specifically, the process of classifying bullet chatting is carried out one by one according to the number of pieces of information. By obtaining the first bullet chat information and inputting the first bullet chat information into the bullet chat classification decision tree, the bullet chat Classify the collection of episodic information. The first bullet chat information belongs to the bullet chat information set, which can be bullet chat information with any content at any time, and the classification result represents the content characteristics of the first bullet chat information, and all bullet chat information is collected in this way By performing classification, a corresponding classification result can be obtained. According to the classification result, an appropriate reply sentence can be matched to facilitate intelligent reply.
进一步地，本申请实施例还包括步骤S900，其中，步骤S900包括：Further, the embodiment of the present application also includes step S900, wherein step S900 includes:
步骤S910：根据所述决策树，获得节点信息；Step S910: Obtain node information according to the decision tree;
步骤S920：根据所述节点信息，获得节点功能特征；Step S920: Obtain node function features according to the node information;
步骤S930：根据所述节点功能特征，对人机交互界面进行分区，获得第一分区结果；Step S930: partition the human-computer interaction interface according to the functional characteristics of the nodes, and obtain the first partition result;
步骤S940：根据所述第一分类结果和所述第一分区结果进行特征匹配，获得第一匹配结果；Step S940: Perform feature matching according to the first classification result and the first partition result to obtain a first matching result;
步骤S950：根据所述第一匹配结果，对所述第一分类结果进行分区显示。Step S950: According to the first matching result, perform partition display on the first classification result.
具体而言，决策树分析法适用的范围有限，当数据过大或数据更新过快时，会导致决策树分析的速度降低甚至展现出滞后性。节点为数据结构树中的分支点，通过节点的连接和分流，不同类别的数据被引入相应的分类集合。所述节点功能特征表示对待分类数据的指定特征，通过所述节点功能特征，对人机交互界面进行分区，获得第一分区结果。对所述第一分类结果和所述第一分区结果进行特征匹配，获得第一匹配结果，所述第一匹配结果是将人机交互界面的分类信息和决策树分析结果进行匹配，达成减小决策树工作量的目的。对人机交互界面分区的过程实质上是对决策树分析进行前置调配的过程，通过对人机交互界面分区，获得第一分区结果，可有效降低决策树工作量，提高工作效率，使得弹幕信息分类的结果更加准确。Specifically, the scope of application of the decision tree analysis method is limited. When the data is too large or the data is updated too quickly, the speed of the decision tree analysis will be reduced or even lag. Nodes are branch points in the data structure tree. Through the connection and shunting of nodes, different types of data are introduced into corresponding classification sets. The node function feature represents the specified feature of the data to be classified, and the human-computer interaction interface is partitioned through the node function feature to obtain the first partition result. Perform feature matching on the first classification result and the first partition result to obtain a first matching result, the first matching result is to match the classification information of the human-computer interaction interface with the decision tree analysis result to achieve a reduction Purpose of Decision Tree Workload. The process of partitioning the human-computer interaction interface is essentially a pre-deployment process for decision tree analysis. By partitioning the human-computer interaction interface and obtaining the first partition result, the workload of the decision tree can be effectively reduced, and work efficiency can be improved. The results of subtext information classification are more accurate.
进一步地，本申请实施例步骤S940还包括：Further, step S940 in this embodiment of the present application also includes:
步骤S941：根据所述节点功能特征，获得功能卷积比对特征集合，其中，所述功能卷积比对特征中的每个功能卷积比对特征与所述第一分区结果中的每个分区相匹配；Step S941: Obtain a functional convolutional comparison feature set according to the node functional features, wherein each of the functional convolutional comparison features is the same as each of the first partition results Partitions match;
步骤S942：根据所述功能卷积比对特征集合中的每个功能卷积比对特征对所述第一分类结果中各类别的弹幕信息进行特征遍历比对，获得第一比对结果；Step S942: According to each functional convolution comparison feature in the functional convolution comparison feature set, perform feature traversal comparison on the barrage information of each category in the first classification result to obtain a first comparison result;
步骤S943：按照所述第一比对结果，将所述第一分类结果中的各类别与所述第一分区结果中的每个分区进行匹配，获得第一匹配结果。Step S943: According to the first comparison result, match each category in the first classification result with each partition in the first partition result to obtain a first matching result.
具体而言，卷积神经网络是一种具有局部连接、权值共享等特点的深层前馈神经网络，在图像和视频分析领域，比如图像分类、目标检测、图像分割等各种视觉任务上取得了显著的效果，是目前应用最广泛的模型之一。卷积神经网络，从字面上包括两个部分：卷积+神经网络。其中，卷积就是特征提取器，而神经网络，可以看作分类器。训练一个卷积神经网络，就是同时训练了特征提取器(卷积)和后面的分类器(神经网络)。分别根据所述功能卷积比对特征集合中的每个功能卷积比对特征对所述第一分类结果中各类别的弹幕信息进行特征遍历比，可获得对应获得第一比对结果，按照所述第一比对结果，将所述第一分类结果中的各类别与所述第一分区结果中的每个分区进行匹配，获得第一匹配结果。所述第一匹配结果是经过卷积神经网络进行特征训练后的结果，用于判断所述第一分类结果与所述第一分区结果的吻合程度。Specifically, the convolutional neural network is a deep feed-forward neural network with the characteristics of local connection and weight sharing. It has achieved remarkable results and is one of the most widely used models at present. Convolutional neural network literally consists of two parts: convolution + neural network. Among them, convolution is a feature extractor, and neural network can be regarded as a classifier. Training a convolutional neural network is to train the feature extractor (convolution) and the subsequent classifier (neural network) at the same time. According to each functional convolution comparison feature in the functional convolution comparison feature set, the feature traversal ratio is performed on the barrage information of each category in the first classification result, and the corresponding first comparison result can be obtained, According to the first comparison result, each category in the first classification result is matched with each partition in the first partition result to obtain a first matching result. The first matching result is a result of feature training performed by a convolutional neural network, and is used to determine the degree of agreement between the first classification result and the first partition result.
进一步地，本申请实施例步骤S700还包括：Further, step S700 in this embodiment of the present application also includes:
步骤S710：如果所述第一分类结果中不存在属于所述自动回复特征库的弹幕信息，获得第一提醒指令，所述第一提醒指令用于提醒主播回复所述弹幕信息；Step S710: if there is no bullet chatting information belonging to the automatic reply feature library in the first classification result, obtain a first reminder instruction, the first reminder instruction is used to remind the host to reply to the bullet chatting information;
步骤S720：根据所述第一提醒信息，获得第一回复信息；Step S720: Obtain first reply information according to the first reminder information;
步骤S730：当获得所述第一回复信息后，获得第二提醒信息，所述第二提醒信息用于提醒第一粉丝收到所述第一回复信息。Step S730: After obtaining the first reply information, obtain second reminder information, the second reminder information is used to remind the first fan to receive the first reply information.
具体而言，观众数量多也会导致弹幕信息多种多样，有的观众会提出较为新颖的问题，所述第一分类结果中不包含相关特征，这种问题不适用于自动回复，而应该通过所述第一提醒指令来提醒主播进行关注并回复，所述第一回复信息即主播通过直播平台直接对弹幕发送者进行回复的内容。为了提高观众的观看体验，及时通知观众查看回复信息，在获得所述第一回复信息后，获得第二提醒信息，所述第二提醒信息用于提醒第一粉丝收到所述第一回复信息。通过自动回复和主播直接回复的方式相结合，达到了提高直播弹幕回复率的效果。Specifically, a large number of viewers will also lead to a variety of barrage information, and some viewers will ask relatively novel questions. The first classification results do not contain relevant features. This kind of question is not suitable for automatic replies, but should be The anchor is reminded to pay attention and reply through the first reminder instruction, and the first reply information is the content that the anchor directly replies to the barrage sender through the live broadcast platform. In order to improve the viewing experience of the audience, the audience is notified in time to check the reply information, and after obtaining the first reply information, second reminder information is obtained, and the second reminder information is used to remind the first fans to receive the first reply information . Through the combination of automatic reply and anchor direct reply, the effect of improving the reply rate of live barrage is achieved.
进一步地，本申请实施例步骤S730还包括：Further, step S730 in this embodiment of the present application also includes:
步骤S731：判断所述第一粉丝是否在线；Step S731: judging whether the first fan is online;
步骤S732：如果所述第一粉丝不在线，对第一回复内容进行录制，获得第一录制内容，将第一录制内容发送至所述第一粉丝。Step S732: If the first fan is not online, record the first reply content, obtain the first recorded content, and send the first recorded content to the first fan.
具体而言，网络直具有实时性，观众有时会因为切换手机界面等原因错过部分直播内容，为了避免观众错过所述第一回复信息，对所述第一粉丝的在线情况进行判断，当所述第一粉丝处于离线状态，及时对第一回复内容进行录制，获得第一录制内容，将第一录制内容发送至所述第一粉丝，确保所述第一粉丝在下一次上线时能够收到所述第一回复信息。通过追踪所述第一粉丝的在线状态并适时发送回复内容，可以避免所述第一粉丝错过想要了解的内容，也间接提高了观众满意度。Specifically, the network has always been real-time, and viewers sometimes miss part of the live broadcast content due to reasons such as switching mobile phone interfaces. In order to prevent viewers from missing the first reply message, the online status of the first fan is judged. The first fan is offline, record the first reply content in time, obtain the first recorded content, send the first recorded content to the first fan, and ensure that the first fan can receive the First reply message. By tracking the online status of the first fan and sending reply content in a timely manner, the first fan can be prevented from missing the content he wants to know, and audience satisfaction is also indirectly improved.
综上所述，本申请实施例所提供的一种基于虚拟现实技术的直播交互方式具有如下技术效果：To sum up, a live interactive mode based on virtual reality technology provided by the embodiment of the present application has the following technical effects:
1、本申请实施例提供了一种基于虚拟现实技术的直播交互方式，其中，所述方式应用于一信息中转平台，所述方式包括：根据信息处理平台收集第一直播间内的弹幕信息集合；根据大数据获得多个弹幕分类特征；根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；根据所述多个信息熵，构建弹幕分类决策树；根据所述弹幕分类决策树，获得第一分类结果；构建自动回复特征库；判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；如果所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复，解决了现有技术中直播观众数量庞大时主播方无法全面且及时对弹幕信息进行反馈导致观众体验不佳的技术问题，通过构建自动回复特征库并对直播弹幕进行智能回复，达到了及时反馈弹幕信息的技术目的，实现了提高直播观感和观众满意度的技术效果，进一步提高了观众黏性，保障了网络直播行业的良好发展。1. The embodiment of the present application provides a live broadcast interaction method based on virtual reality technology, wherein the method is applied to an information transfer platform, and the method includes: collecting barrage information in the first live broadcast room according to the information processing platform Set; obtain a plurality of barrage classification features according to the big data; classify the barrage information collection according to the plurality of barrage classification features, and perform information theory coding operations to obtain a plurality of information entropies; according to the plurality of information Entropy, constructing a barrage classification decision tree; according to the barrage classification decision tree, obtaining the first classification result; constructing an automatic reply feature library; judging whether there is a barrage belonging to the automatic reply feature library in the first classification result information; if there is bullet chat information belonging to the automatic reply feature library in the first classification result, the bullet chat information belonging to the automatic reply feature library is automatically replied according to the automatic reply feature library, which solves the existing problem In technology, when the number of live broadcast viewers is huge, the anchor cannot provide comprehensive and timely feedback on the barrage information, resulting in poor audience experience. By building an automatic reply feature library and intelligently replying to the live barrage information, timely feedback on the barrage information is achieved. The technical purpose is to achieve the technical effect of improving the live broadcast perception and audience satisfaction, further improving the audience stickiness, and ensuring the sound development of the online live broadcast industry.
2、通过获得功能卷积比对特征集合，并根据所述功能卷积比对特征集合中的每个功能卷积比对特征对所述第一分类结果中各类别的弹幕信息进行特征遍历比对，获得第一匹配结果，所述第一匹配结果是经过卷积神经网络进行特征训练后的结果，用于判断所述第一分类结果与所述第一分区结果的吻合程度。通过使用卷积神经网络实现所述第一匹配结果的获取，提高了所述第一分区结果和所述第一分类结果匹配的准确性。2. By obtaining the functional convolution comparison feature set, and performing feature traversal on the barrage information of each category in the first classification result according to each functional convolution comparison feature in the functional convolution comparison feature set Comparing to obtain a first matching result, the first matching result is a result of feature training performed by a convolutional neural network, and is used to judge the degree of agreement between the first classification result and the first partition result. Acquiring the first matching result by using a convolutional neural network improves the matching accuracy of the first partitioning result and the first classification result.
实施例二Embodiment two
基于与前述实施例中一种基于虚拟现实技术的直播交互方式同样发明构思，本发明还提供了一种基于虚拟现实技术的直播交互系统，如图2所示，所述系统包括：Based on the same inventive idea as the live broadcast interaction method based on virtual reality technology in the foregoing embodiments, the present invention also provides a live broadcast interaction system based on virtual reality technology, as shown in FIG. 2 , the system includes:
第一收集单元11，所述第一收集单元11用于根据信息处理平台收集第一直播间内的弹幕信息集合；The
第一获得单元12，所述第一获得单元12用于根据大数据获得多个弹幕分类特征；The first obtaining
第二获得单元13，所述第二获得单元13用于根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；The second obtaining
第一构建单元14，所述第一构建单元14用于根据所述多个信息熵，构建弹幕分类决策树；The
第三获得单元15，所述第三获得单元15用于根据所述弹幕分类决策树，获得第一分类结果；A third obtaining
第二构建单元16，所述第二构建单元16用于构建自动回复特征库；The
第一判断单元17，所述第一判断单元17用于判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；The
第一执行单元18，所述第一执行单元18用于当所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复。The
进一步地，所述系统还包括：Further, the system also includes:
第四获得单元，所述第四获得单元用于将所述多个信息熵输入数值大小比对模型，获得第一根节点特征信息；A fourth obtaining unit, the fourth obtaining unit is used to input the plurality of information entropies into the numerical size comparison model to obtain the characteristic information of the first root node;
第三构建单元，所述第三构建单元用于基于递归算法，对所述第一根节点特征信息和所述弹幕信息集合进行计算，构建所述弹幕分类决策树。A third construction unit, the third construction unit is configured to calculate the feature information of the first root node and the bullet chatting information set based on a recursive algorithm, and construct the bullet chatting classification decision tree.
进一步地，所述装置还包括：Further, the device also includes:
第五获得单元，所述第五获得单元用于获得第一弹幕信息，所述第一弹幕信息属于所述弹幕信息集合；A fifth obtaining unit, the fifth obtaining unit is used to obtain first bullet chat information, and the first bullet chat information belongs to the bullet chat information set;
第六获得单元，所述第六获得单元用于将所述第一弹幕信息输入所述弹幕分类决策树，对所述弹幕信息集合进行分类，获得所述第一分类结果。A sixth obtaining unit, configured to input the first bullet chat information into the bullet chat classification decision tree, classify the bullet chat information set, and obtain the first classification result.
进一步地，所述装置还包括：Further, the device also includes:
第七获得单元，所述第七获得单元用于根据所述决策树，获得节点信息；A seventh obtaining unit, the seventh obtaining unit is used to obtain node information according to the decision tree;
第八获得单元，所述第八获得单元用于根据所述节点信息，获得节点功能特征；An eighth obtaining unit, the eighth obtaining unit is configured to obtain node function features according to the node information;
第九获得单元，所述第九获得单元用于根据所述节点功能特征，对人机交互界面进行分区，获得第一分区结果；A ninth obtaining unit, the ninth obtaining unit is used to partition the human-computer interaction interface according to the functional characteristics of the node, and obtain the first partition result;
第十获得单元，所述第十获得单元用于根据所述第一分类结果和所述第一分区结果进行特征匹配，获得第一匹配结果；A tenth obtaining unit, the tenth obtaining unit is configured to perform feature matching according to the first classification result and the first partition result to obtain a first matching result;
第二执行单元，所述第二执行单元用于根据所述第一匹配结果，对所述第一分类结果进行分区显示。A second execution unit, configured to perform partition display on the first classification result according to the first matching result.
进一步地，所述装置还包括：Further, the device also includes:
第十一获得单元，所述第十一获得单元用于根据所述节点功能特征，获得功能卷积比对特征集合，其中，所述功能卷积比对特征中的每个功能卷积比对特征与所述第一分区结果中的每个分区相匹配；An eleventh obtaining unit, the eleventh obtaining unit is used to obtain a functional convolution comparison feature set according to the node functional characteristics, wherein each functional convolution comparison feature in the functional convolution comparison features features are matched to each partition in said first partition result;
第十二获得单元，所述第十二获得单元用于根据所述功能卷积比对特征集合中的每个功能卷积比对特征对所述第一分类结果中各类别的弹幕信息进行特征遍历比对，获得第一比对结果；The twelfth obtaining unit, the twelfth obtaining unit is used to perform the barrage information of each category in the first classification result according to each function convolution comparison feature in the function convolution comparison feature set Feature traversal comparison to obtain the first comparison result;
第十三获得单元，所述第十三获得单元用于按照所述第一比对结果，将所述第一分类结果中的各类别与所述第一分区结果中的每个分区进行匹配，获得第一匹配结果。A thirteenth obtaining unit, the thirteenth obtaining unit is configured to match each category in the first classification result with each partition in the first partition result according to the first comparison result, Get the first matching result.
进一步地，所述装置还包括：Further, the device also includes:
第十四获得单元，所述第十四获得单元用于如果所述第一分类结果中不存在属于所述自动回复特征库的弹幕信息，获得第一提醒指令，所述第一提醒指令用于提醒主播回复所述弹幕信息；A fourteenth obtaining unit, the fourteenth obtaining unit is used to obtain a first reminder instruction if there is no barrage information belonging to the automatic reply feature library in the first classification result, and the first reminder instruction is used To remind the anchor to reply to the barrage information;
第十五获得单元，所述第十五获得单元用于根据所述第一提醒信息，获得第一回复信息；A fifteenth obtaining unit, the fifteenth obtaining unit is configured to obtain first reply information according to the first reminder information;
第十六获得单元，所述第十六获得单元用于当获得所述第一回复信息后，获得第二提醒信息，所述第二提醒信息用于提醒第一粉丝收到所述第一回复信息。A sixteenth obtaining unit, the sixteenth obtaining unit is used to obtain second reminder information after obtaining the first reply information, and the second reminder information is used to remind the first fan to receive the first reply information.
进一步地，所述装置还包括：Further, the device also includes:
第二判断单元，所述第二判断单元用于判断所述第一粉丝是否在线；A second judging unit, the second judging unit is used to judge whether the first fan is online;
第十七获得单元，所述第十七获得单元用于如果所述第一粉丝不在线，对第一回复内容进行录制，获得第一录制内容，将第一录制内容发送至所述第一粉丝。A seventeenth obtaining unit, the seventeenth obtaining unit is used to record the first reply content if the first fan is not online, obtain the first recorded content, and send the first recorded content to the first fan .
前述图1实施例一中的基于虚拟现实技术的直播交互方式和具体实例同样适用于本实施例的基于虚拟现实技术的直播交互系统，通过前述对基于虚拟现实技术的直播交互方式的详细描述，本领域技术人员可以清楚地知道本实施例中基于虚拟现实技术的直播交互系统，所以为了说明书的简洁，在此不再详述。The above-mentioned virtual reality technology-based live broadcast interaction method and specific examples in the first embodiment of FIG. 1 are also applicable to the virtual reality technology-based live broadcast interaction system of this embodiment. Through the foregoing detailed description of the virtual reality technology-based live broadcast interaction method, Those skilled in the art can clearly know the live interactive system based on virtual reality technology in this embodiment, so for the sake of brevity of the description, details are not described here.
示例性电子设备Exemplary electronic device
下面参考图3来描述本申请实施例的电子设备。The electronic device according to the embodiment of the present application is described below with reference to FIG. 3 .
图3图示了根据本申请实施例的电子设备的结构示意图。Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
基于与前述实施例中一种基于虚拟现实技术的直播交互方式的发明构思，本发明还提供一种基于虚拟现实技术的直播交互系统，其上存储有计算机程序，该程序被处理器执行时实现前文所述一种基于虚拟现实技术的直播交互方式的任一方法的步骤。Based on the inventive concept of a live broadcast interaction method based on virtual reality technology in the foregoing embodiments, the present invention also provides a live broadcast interactive system based on virtual reality technology, on which a computer program is stored, and the program is implemented when executed by a processor. The steps of any method of a live interactive method based on virtual reality technology described above.
其中，在图3中，总线架构(用总线300来代表)，总线300可以包括任意数量的互联的总线和桥，总线300将包括由处理器302代表的一个或多个处理器和存储器304代表的存储器的各种电路连接在一起。总线300还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路连接在一起，这些都是本领域所公知的，因此，本文不再对其进行进一步描述。总线接口305在总线300和接收器301和发送器303之间提供接口。接收器301和发送器303可以是同一个元件，即收发机，提供用于在传输介质上与各种其他装置通信的单元。Wherein, in FIG. 3, the bus architecture (represented by bus 300),
处理器302负责管理总线300和通常的处理，而存储器304可以被用于存储处理器302在执行操作时所使用的数据。
本申请提供了一种基于虚拟现实技术的直播交互方式，其中，所述方式应用于一信息中转平台，所述方式包括：根据信息处理平台收集第一直播间内的弹幕信息集合；根据大数据获得多个弹幕分类特征；根据所述多个弹幕分类特征对所述弹幕信息集合进行分类，并进行信息论编码运算，获得多个信息熵；根据所述多个信息熵，构建弹幕分类决策树；根据所述弹幕分类决策树，获得第一分类结果；构建自动回复特征库；判断所述第一分类结果中是否存在属于所述自动回复特征库的弹幕信息；如果所述第一分类结果中存在属于所述自动回复特征库的弹幕信息，根据所述自动回复特征库对属于所述自动回复特征库的弹幕信息进行自动回复。The present application provides a live broadcast interaction method based on virtual reality technology, wherein the method is applied to an information transfer platform, and the method includes: collecting the barrage information collection in the first live broadcast room according to the information processing platform; The data obtains a plurality of barrage classification features; according to the plurality of barrage classification features, the barrage information collection is classified, and an information theory coding operation is performed to obtain a plurality of information entropies; according to the plurality of information entropies, construct a barrage Screen classification decision tree; According to the bullet chat classification decision tree, obtain the first classification result; Build the automatic reply feature library; Judge whether there is bullet chat information belonging to the described automatic reply feature library in the first classification result; The bullet chat information belonging to the automatic reply feature database exists in the first classification result, and the bullet chat information belonging to the automatic reply feature database is automatically replied according to the automatic reply feature database.
本领域内的技术人员应明白，本发明的实施例可提供为方法、装置或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, apparatuses or computer program products. Accordingly, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
本发明是参照本发明实施例的方法、设备(系统)，和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框，以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的系统。The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a A system for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令系统的制造品，该指令系统实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising a system of instructions, the The system implements the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。尽管已描述了本发明的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明范围的所有变更和修改。These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams. While preferred embodiments of the invention have been described, additional changes and modifications to these embodiments can be made by those skilled in the art once the basic inventive concept is appreciated. Therefore, it is intended that the appended claims be construed to cover the preferred embodiment as well as all changes and modifications which fall within the scope of the invention.
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.
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| CN113641937B (en)* | 2021-08-17 | 2023-06-30 | 杭州时趣信息技术有限公司 | Comment automatic reply method, comment automatic reply system and storage medium |
| CN113923839A (en)* | 2021-10-19 | 2022-01-11 | 苏州爱果乐科技有限公司 | Light adjusting method and system |
| CN115515016B (en)* | 2022-11-04 | 2023-03-31 | 广东玄润数字信息科技股份有限公司 | Virtual live broadcast method, system and storage medium capable of realizing self-cross reply |
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