CN115119013B - Multi-level data machine control application system - Google Patents
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- CN115119013B CN115119013B CN202210308266.7A CN202210308266A CN115119013B CN 115119013 B CN115119013 B CN 115119013B CN 202210308266 A CN202210308266 A CN 202210308266A CN 115119013 B CN115119013 B CN 115119013B
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Abstract
The invention relates to a multistage data machine control application system, which comprises: the relation reconstruction device is used for realizing multiple learning operations on the single-layer neural network by adopting video types corresponding to a plurality of short video contents and corresponding frame-by-frame video pictures as multiple learning data of the single-layer neural network; and the network application equipment is used for taking a plurality of final push pictures corresponding to a plurality of video pictures of a certain short video content of the server which is newly input with the short video as a plurality of input data of the network, and acquiring output data of the network to be taken as a video type corresponding to the certain short video content. The multistage data machine control application system is stable in operation and simple and convenient to operate. Because a single-layer neural network can be introduced to establish a mapping relation between short video framing data and short video types, the corresponding video type of each short video content of a server newly inputting the short video is determined, so that frequent manual video selection operation is reduced.
Description
Technical Field
The invention relates to the field of computer control, in particular to a multistage data machine control application system.
Background
A computer control system (Computer Control System, abbreviated to CCS) is a system which is composed of a control object by using a computer to participate in the control and by means of auxiliary components to obtain a certain control purpose. Computers herein are typically referred to as computers, and can be of various scales, such as general purpose or special purpose computers ranging from micro to mainframe computers. In the prior art, in data management of short video contents, for short video contents that users dislike, screening processing is generally prone to be completed before pushing to users, so that manual switching operation of users is reduced, however, each short video content of a server newly inputting short video cannot determine its corresponding video type, and subsequent short video screening processing cannot be implemented.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a multistage data machine control application system which can introduce a single-layer neural network to establish a mapping relation between short video framing data and short video types, so as to determine the corresponding video type for each short video content of a server newly inputting short videos, and facilitate the subsequent execution of corresponding short video screening processing.
According to an aspect of the present invention, there is provided a multi-level data machine control application system, the system comprising:
the signal capturing device is connected with the short video server and is used for acquiring the video type corresponding to each short video content and the corresponding frame-by-frame video picture;
the primary pushing device is connected with the signal capturing device and used for executing bicubic interpolation action on each frame of video picture of the received short video content so as to obtain a corresponding primary pushing picture;
the intermediate push device is connected with the primary push device and is used for executing morphological operation action on the received primary push picture so as to obtain a corresponding intermediate push picture;
the final stage pushing device is connected with the middle stage pushing device and is used for executing a midpoint filtering action on the received middle stage pushing picture so as to obtain a corresponding final stage pushing picture;
the mapping establishment device is connected with the final-stage pushing device and is used for selecting a plurality of input data of the single-layer neural network as a plurality of final-stage pushing pictures corresponding to a plurality of video pictures of each short video content respectively, and selecting output data of the single-layer neural network as a video type corresponding to the short video content so as to establish a mapping relation between the video picture data of the short video content and the video type;
the relation reconstruction device is connected with the mapping establishment device and is used for realizing multiple learning operations on the single-layer neural network by adopting video types corresponding to a plurality of short video contents and corresponding frame-by-frame video pictures as multiple learning data of the single-layer neural network established by the mapping establishment device;
the network application equipment is connected with the relation reconstruction equipment and is used for taking a plurality of final push pictures corresponding to a plurality of video pictures of a certain short video content of a server which is newly input with the short video as a plurality of input data of a single-layer neural network after the relation reconstruction equipment finishes multiple learning operations, operating the single-layer neural network after the multiple learning operations are finished, and acquiring output data of the single-layer neural network after the multiple learning operations are finished to serve as a video type corresponding to the certain short video content of the server which is newly input with the short video and serve as a target video type to be output;
the primary pushing device, the middle pushing device, the final pushing device, the mapping establishing device and the relation reconstructing device are respectively realized by adopting different computer controllers.
The multistage data machine control application system is stable in operation and simple and convenient to operate. Because a single-layer neural network can be introduced to establish a mapping relation between short video framing data and short video types, the corresponding video type of each short video content of a server newly inputting the short video is determined, so that frequent manual video selection operation is reduced.
The invention has the following remarkable technical progress:
(1) Taking a plurality of content optimization pictures corresponding to a plurality of video pictures of a certain short video content of a server which is newly input with short videos as a plurality of input data of a single-layer neural network after a plurality of learning operations are completed, operating the single-layer neural network after the plurality of learning operations are completed, and acquiring output data of the single-layer neural network after the plurality of learning operations are completed to serve as a video type corresponding to a certain short video content of the server which is newly input with short videos and output as a target video type;
(2) The total number of the plurality of input data of the single-layer neural network is monotonically and positively correlated with the total number of video types managed by the server of the short video;
(3) The smaller the number of short video contents existing in the server of the short video, the smaller the number of times of performing learning operations on the single-layer neural network.
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Embodiments of the present invention will be described below with reference to the accompanying drawings, in which:
fig. 1 is a block diagram illustrating a structure of a multi-level data-controlled application system according to an embodiment of the present invention.
Detailed Description
Embodiments of the multi-level data-based robotic application of the present invention will be described in detail below.
The artificial neural network is a technical reproduction of the biological neural network in a certain simplified sense, and is mainly used for constructing a practical artificial neural network model according to the principle of the biological neural network and the actual application requirement, designing a corresponding learning algorithm, simulating certain intelligent activities of the human brain and then realizing the artificial neural network in the technical way so as to solve the actual problem. In the prior art, in data management of short video contents, for short video contents that users dislike, screening processing is generally prone to be completed before pushing to users, so that manual switching operation of users is reduced, however, each short video content of a server newly inputting short video cannot determine its corresponding video type, and subsequent short video screening processing cannot be implemented.
In order to overcome the defects, the invention discloses a multistage data machine control application system which can effectively solve the corresponding technical problems.
The invention has the following remarkable technical progress:
(1) Taking a plurality of content optimization pictures corresponding to a plurality of video pictures of a certain short video content of a server which is newly input with short videos as a plurality of input data of a single-layer neural network after a plurality of learning operations are completed, operating the single-layer neural network after the plurality of learning operations are completed, and acquiring output data of the single-layer neural network after the plurality of learning operations are completed to serve as a video type corresponding to a certain short video content of the server which is newly input with short videos and output as a target video type;
(2) The total number of the plurality of input data of the single-layer neural network is monotonically and positively correlated with the total number of video types managed by the server of the short video;
(3) The smaller the number of short video contents existing in the server of the short video, the smaller the number of times of performing learning operations on the single-layer neural network.
Fig. 1 is a block diagram illustrating a structure of a multi-level data-controlled application system according to an embodiment of the present invention, the system including:
the signal capturing device is connected with the short video server and is used for acquiring the video type corresponding to each short video content and the corresponding frame-by-frame video picture;
the primary pushing device is connected with the signal capturing device and used for executing bicubic interpolation action on each frame of video picture of the received short video content so as to obtain a corresponding primary pushing picture;
the intermediate push device is connected with the primary push device and is used for executing morphological operation action on the received primary push picture so as to obtain a corresponding intermediate push picture;
the final stage pushing device is connected with the middle stage pushing device and is used for executing a midpoint filtering action on the received middle stage pushing picture so as to obtain a corresponding final stage pushing picture;
the mapping establishment device is connected with the final-stage pushing device and is used for selecting a plurality of input data of the single-layer neural network as a plurality of final-stage pushing pictures corresponding to a plurality of video pictures of each short video content respectively, and selecting output data of the single-layer neural network as a video type corresponding to the short video content so as to establish a mapping relation between the video picture data of the short video content and the video type;
the relation reconstruction device is connected with the mapping establishment device and is used for realizing multiple learning operations on the single-layer neural network by adopting video types corresponding to a plurality of short video contents and corresponding frame-by-frame video pictures as multiple learning data of the single-layer neural network established by the mapping establishment device;
the network application equipment is connected with the relation reconstruction equipment and is used for taking a plurality of final push pictures corresponding to a plurality of video pictures of a certain short video content of a server which is newly input with the short video as a plurality of input data of a single-layer neural network after the relation reconstruction equipment finishes multiple learning operations, operating the single-layer neural network after the multiple learning operations are finished, and acquiring output data of the single-layer neural network after the multiple learning operations are finished to serve as a video type corresponding to the certain short video content of the server which is newly input with the short video and serve as a target video type to be output;
the primary pushing device, the middle pushing device, the final pushing device, the mapping establishing device and the relation reconstructing device are respectively realized by adopting different computer controllers.
Next, a further explanation of the specific structure of the multi-level data machine control application system of the present invention will be continued.
The multi-level data machine control application system may further include:
and the content recommending device is connected with the network application device and is used for listing the short video content corresponding to the acquired target video type into a recommended video queue as a recommended video when the acquired target video type is matched with the video type preferred by the current user.
The multi-level data machine control application system may further include:
the queue storage mechanism is connected with the content pushing device and used for storing a recommended video queue, and the recommended video queue adopts a first-in first-out storage mode.
The multi-level data machine control application system comprises:
selecting a plurality of input data of a single-layer neural network as a plurality of final push pictures corresponding to a plurality of video pictures of each short video content respectively, and selecting output data of the single-layer neural network as a video type corresponding to the short video content to establish a mapping relation between video picture data of the short video content and the video type comprises: the total number of the plurality of input data of the single-layer neural network is monotonically positively associated with the total number of server-managed video types of the short video.
The multi-level data machine control application system comprises:
the method for realizing multiple learning operations on the single-layer neural network by adopting video types corresponding to the short video contents and corresponding frame-by-frame video pictures as multiple learning data of the single-layer neural network established by the mapping establishment equipment comprises the following steps: the smaller the number of short video contents existing in the server of the short video, the fewer the number of times of learning operations performed on the single-layer neural network.
The multi-level data machine control application system comprises:
the primary push device, the intermediate push device, the final push device, the map creation device, and the relationship reconstruction device share the same clock generation device.
The multi-level data machine control application system comprises:
the primary push device, the intermediate push device, the final push device, the map creation device, and the relationship reconstruction device share the same voltage conversion device.
The multi-level data machine control application system comprises:
the primary push device, the intermediate push device, the final push device, the map creation device, and the relationship reconstruction device share the same parallel data bus.
In the multi-level data machine control application system:
taking a plurality of final push pictures respectively corresponding to a plurality of video pictures of a certain short video content of a server which inputs short videos newly as a plurality of input data of a single-layer neural network after the repeated learning operation is completed by the relational reconstruction equipment, operating the single-layer neural network after the repeated learning operation is completed, acquiring output data of the single-layer neural network after the repeated learning operation is completed as a video type corresponding to a certain short video content of the server which inputs short videos newly, and outputting the video type as a target video type, wherein the method comprises the following steps: the target video type is one of action, adventure, comedy, scenario, fantasy, horror, love and history.
And in the multi-level data machine control application system:
selecting a plurality of input data of a single-layer neural network as a plurality of final push pictures corresponding to a plurality of video pictures of each short video content respectively, and selecting output data of the single-layer neural network as a video type corresponding to the short video content to establish a mapping relation between video picture data of the short video content and the video type comprises: the single layer neural network includes an input layer and an output layer.
In addition, the multistage data machine control application system can further comprise a data temporary storage chip which is respectively connected with the primary pushing device, the middle pushing device, the final pushing device, the mapping establishment equipment and the relation reconstruction equipment;
the data temporary storage chip is used for temporarily storing input data and output data of the primary pushing device, the middle pushing device, the final pushing device, the mapping establishing equipment and the relation reconstructing equipment respectively.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus/electronic device/computer readable storage medium/computer program product embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.
Claims (8)
1. A multi-level data machine control application system, the system comprising:
the signal capturing device is connected with the short video server and is used for acquiring the video type corresponding to each short video content and the corresponding frame-by-frame video picture;
the primary pushing device is connected with the signal capturing device and used for executing bicubic interpolation action on each frame of video picture of the received short video content so as to obtain a corresponding primary pushing picture;
the intermediate push device is connected with the primary push device and is used for executing morphological operation action on the received primary push picture so as to obtain a corresponding intermediate push picture;
the final stage pushing device is connected with the middle stage pushing device and is used for executing a midpoint filtering action on the received middle stage pushing picture so as to obtain a corresponding final stage pushing picture;
the mapping establishment device is connected with the final-stage pushing device and is used for selecting a plurality of input data of the single-layer neural network as a plurality of final-stage pushing pictures corresponding to a plurality of video pictures of each short video content respectively, and selecting output data of the single-layer neural network as a video type corresponding to the short video content so as to establish a mapping relation between the video picture data of the short video content and the video type;
the relation reconstruction device is connected with the mapping establishment device and is used for realizing multiple learning operations on the single-layer neural network by adopting video types corresponding to a plurality of short video contents and corresponding frame-by-frame video pictures as multiple learning data of the single-layer neural network established by the mapping establishment device;
the network application equipment is connected with the relation reconstruction equipment and is used for taking a plurality of final push pictures corresponding to a plurality of video pictures of a certain short video content of a server which is newly input with the short video as a plurality of input data of a single-layer neural network after the relation reconstruction equipment finishes multiple learning operations, operating the single-layer neural network after the multiple learning operations are finished, and acquiring output data of the single-layer neural network after the multiple learning operations are finished to serve as a video type corresponding to the certain short video content of the server which is newly input with the short video and serve as a target video type to be output;
the primary pushing device, the middle pushing device, the final pushing device, the mapping establishing equipment and the relation reconstructing equipment are respectively realized by adopting different computer controllers;
selecting a plurality of input data of a single-layer neural network as a plurality of final push pictures corresponding to a plurality of video pictures of each short video content respectively, and selecting output data of the single-layer neural network as a video type corresponding to the short video content to establish a mapping relation between video picture data of the short video content and the video type comprises: the total number of the plurality of input data of the single-layer neural network is monotonically and positively correlated with the total number of video types managed by the server of the short video;
the method for realizing multiple learning operations on the single-layer neural network by adopting video types corresponding to the short video contents and corresponding frame-by-frame video pictures as multiple learning data of the single-layer neural network established by the mapping establishment equipment comprises the following steps: the fewer the number of short video contents existing in the short video server, the fewer the number of times of learning operation performed on the single-layer neural network;
the data temporary storage chip is respectively connected with the primary pushing device, the middle pushing device, the final pushing device, the mapping establishing equipment and the relation reconstructing equipment; the data temporary storage chip is used for temporarily storing input data and output data of the primary pushing device, the middle pushing device, the final pushing device, the mapping establishing equipment and the relation reconstructing equipment respectively.
2. The multi-level data machine control application system of claim 1, wherein the system further comprises:
and the content recommending device is connected with the network application device and is used for listing the short video content corresponding to the acquired target video type into a recommended video queue as a recommended video when the acquired target video type is matched with the video type preferred by the current user.
3. The multi-level data machine control application system of claim 2, wherein the system further comprises:
the queue storage mechanism is connected with the content recommendation device and used for storing a recommended video queue, and the recommended video queue adopts a first-in first-out storage mode.
4. A multi-level data machine control application system as claimed in any one of claims 1 to 3, wherein:
the primary push device, the intermediate push device, the final push device, the map creation device, and the relationship reconstruction device share the same clock generation device.
5. A multi-level data machine control application system as claimed in any one of claims 1 to 3, wherein:
the primary push device, the intermediate push device, the final push device, the map creation device, and the relationship reconstruction device share the same voltage conversion device.
6. A multi-level data machine control application system as claimed in any one of claims 1 to 3, wherein:
the primary push device, the intermediate push device, the final push device, the map creation device, and the relationship reconstruction device share the same parallel data bus.
7. A multi-level data machine control application system as claimed in any one of claims 1 to 3, wherein:
taking a plurality of final push pictures respectively corresponding to a plurality of video pictures of a certain short video content of a server which inputs short videos newly as a plurality of input data of a single-layer neural network after the repeated learning operation is completed by the relational reconstruction equipment, operating the single-layer neural network after the repeated learning operation is completed, acquiring output data of the single-layer neural network after the repeated learning operation is completed as a video type corresponding to a certain short video content of the server which inputs short videos newly, and outputting the video type as a target video type, wherein the method comprises the following steps: the target video type is one of action, adventure, comedy, scenario, fantasy, horror, love and history.
8. A multi-level data machine control application system as claimed in any one of claims 1 to 3, wherein:
selecting a plurality of input data of a single-layer neural network as a plurality of final push pictures corresponding to a plurality of video pictures of each short video content respectively, and selecting output data of the single-layer neural network as a video type corresponding to the short video content to establish a mapping relation between video picture data of the short video content and the video type comprises: the single layer neural network includes an input layer and an output layer.
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| CN108985244B (en) * | 2018-07-24 | 2021-10-15 | 海信集团有限公司 | Television program type identification method and device |
| CN110110626A (en) * | 2019-04-24 | 2019-08-09 | 北京奇艺世纪科技有限公司 | A kind of video feeling classification recognition methods, device and electronic equipment |
| CN110070067B (en) * | 2019-04-29 | 2021-11-12 | 北京金山云网络技术有限公司 | Video classification method, training method and device of video classification method model and electronic equipment |
| CN111382309B (en) * | 2020-03-10 | 2023-04-18 | 深圳大学 | Short video recommendation method based on graph model, intelligent terminal and storage medium |
| CN113536840A (en) * | 2020-04-15 | 2021-10-22 | 北京金山云网络技术有限公司 | Video classification method, device, equipment and storage medium |
| CN112989116B (en) * | 2021-05-10 | 2021-10-26 | 广州筷子信息科技有限公司 | Video recommendation method, system and device |
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