CN110597854A - Data classification method based on FE industrial internet and related products - Google Patents
Data classification method based on FE industrial internet and related products Download PDFInfo
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- CN110597854A CN110597854A CN201910722506.6A CN201910722506A CN110597854A CN 110597854 A CN110597854 A CN 110597854A CN 201910722506 A CN201910722506 A CN 201910722506A CN 110597854 A CN110597854 A CN 110597854A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2228—Indexing structures
- G06F16/2255—Hash tables
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24553—Query execution of query operations
- G06F16/24554—Unary operations; Data partitioning operations
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Abstract
The present disclosure provides a data classification method based on an FE industrial internet and a related product, the method including: the intelligent equipment receives data sent by the industrial Internet; the intelligent equipment inputs the data into an AI classifier to carry out classification operation to obtain a first class of the data; the intelligent device carries out hash operation on the data to obtain a first hash value, searches whether the first hash value exists in the first category, if so, adds a timestamp of the data in notes of the first hash value. The technical scheme provided by the application has the advantage of saving the storage space.
Description
Technical Field
The invention relates to the technical field of networks, in particular to a data classification method based on an FE industrial internet and a related product.
Background
The industrial internet is connected with human-computer through intelligent machine connection, combines software and big data analysis, reconstructs global industry, stimulates productivity, and makes the world better, faster, safer, cleaner and more economical.
Industrial internets, such as the FE industrial internet, are an industrial internet created for an enterprise FE, and for the industrial internet, there are a large amount of data, and at present, a large amount of data is not classified, so that the large amount of data is not only hard to manage, but also greatly affects storage resources.
Disclosure of Invention
The embodiment of the invention provides a data classification method based on an FE industrial internet and a related product, which can realize the advantages of classifying industrial internet data, facilitating data processing and optimizing storage resources.
In a first aspect, an embodiment of the present invention provides a data classification method based on an FE industrial internet, where the method includes the following steps:
the intelligent equipment receives data sent by the industrial Internet;
the intelligent equipment inputs the data into an AI classifier to carry out classification operation to obtain a first class of the data;
the intelligent device carries out hash operation on the data to obtain a first hash value, searches whether the first hash value exists in the first category, if so, adds a timestamp of the data in notes of the first hash value.
Optionally, the method further includes:
the intelligent device receives an extraction command of data, the extraction command comprises a time stamp, the intelligent device inquires a first hash value corresponding to the time stamp from a database of the first category, and data corresponding to the first hash value are extracted.
Optionally, the step of inputting the data into the AI classifier by the intelligent device to perform classification operation to obtain the first category of the data specifically includes:
the intelligent device inputs the data serving as input data into the to-be-AI classifier to execute n layers of convolution operation to obtain a convolution operation result, executes full-connection operation on the convolution operation result to obtain a full-connection result, and determines the first category according to the full-connection result.
Optionally, the method further includes:
and the intelligent equipment sends the first class to the manual confirmation, receives a second class replied manually, and retrains and updates the AI classifier if the second class is different from the first class.
In a second aspect, a terminal is provided, which includes:
the receiving and sending unit is used for receiving data sent by the industrial Internet;
the processing unit is used for inputting the data into the AI classifier to carry out classification operation to obtain a first class of the data; and performing hash operation on the data to obtain a first hash value, searching whether the first hash value exists in the first category, if so, adding a timestamp of the data in a note of the first hash value to receive a first command sent by the first terminal, and controlling an interface of the second terminal according to the first command.
Optionally, the transceiver unit is configured to receive an extraction command of data;
and the processing unit is used for inquiring a first hash value corresponding to the time stamp from the database of the first category and extracting data corresponding to the first hash value, wherein the extracting command contains the time stamp.
Optionally, the processing unit is specifically configured to input the data as input data into a to-be-AI classifier to perform n layers of convolution operations to obtain a convolution operation result, perform full join operation on the convolution operation result to obtain a full join result, and determine the first category according to the full join result.
Optionally, the transceiver unit is further configured to send the first category to a manual confirmation, and receive a second category of a manual reply;
and the processing unit is used for retraining and updating the AI classifier if the second class is different from the first class.
Optionally, the terminal is: a smartphone, a tablet, a computer, or a server.
In a third aspect, a computer-readable storage medium is provided, which stores a program for electronic data exchange, wherein the program causes a terminal to execute the method provided in the first aspect.
The embodiment of the invention has the following beneficial effects:
it can be seen that, after receiving data, the technical solution provided by the present application performs classification processing on the data to determine the first category, and then searches whether there is data that is the same as the data in the database of the first category, and in order to reduce the search amount, here, the search is implemented by using a hash value, and if it is determined that there is the same hash value, the recording of the data is implemented by directly adding a timestamp of the data in a remark of the hash value, so that the data does not need to be stored, and the utilization rate of the storage space is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a terminal.
Fig. 2 is a flow chart diagram of a data classification method based on the FE industrial internet.
Fig. 3 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of the invention and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively 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, result, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase 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. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
A, B in this application are merely symbols, which are different and have no practical meaning, and reference numbers such as "S101" and "S102" in this application do not represent a logical order of execution.
Referring to fig. 1, fig. 1 provides an intelligent device, where the intelligent device may be a terminal of an IOS system, an android system, a windows system, and the terminal specifically may include: the device comprises a processor, a memory, a communication module and a display screen, wherein the above components may be connected through a bus or in other ways. And the plurality of intelligent devices form an industrial internet and are communicated with a remote internet. This manner of connectivity may be implemented by one or more of the plurality of smart devices.
Referring to fig. 2, fig. 2 provides a data classification method based on the FE industrial internet, where the method is shown in fig. 2 and is performed by the intelligent device shown in fig. 1, and the method includes the following steps:
step S201, the intelligent device receives data sent by an industrial internet;
step S202, the intelligent device inputs the data into an AI classifier to perform classification operation to obtain a first class of the data;
step S203, the intelligent device performs a hash operation on the data to obtain a first hash value, searches whether the first hash value exists in the first category, and adds a timestamp of the data in a note of the first hash value if the first hash value exists.
After receiving data, the technical scheme provided by the application classifies the data to determine the first category, then searches whether the data identical to the data exists in the database of the first category, in order to reduce the search amount, the search is realized through the hash value, if the data are determined to have the identical hash value, the data recording is realized by directly adding the timestamp of the data in the remark of the hash value, so that the data do not need to be stored, and the utilization rate of the storage space is improved.
The technical scheme mainly aims at realizing storage aiming at a plurality of same commands, for the FE industrial Internet, most of the commands are the same commands due to relatively fixed operation, and for the same commands, only corresponding timestamps need to be recorded during data recording, so that the corresponding storage space can be saved, and query and search are easy.
Optionally, the method may further include:
the intelligent device receives an extraction command of data, the extraction command comprises a time stamp, the intelligent device inquires a first hash value corresponding to the time stamp from a database of the first category, and data corresponding to the first hash value are extracted.
The technical scheme realizes the extraction of data.
Optionally, the step of inputting the data into the AI classifier by the intelligent device to perform classification operation to obtain the first category of the data may specifically include:
the intelligent device inputs the data serving as input data into the to-be-AI classifier to execute n layers of convolution operation to obtain a convolution operation result, executes full-connection operation on the convolution operation result to obtain a full-connection result, and determines the first category according to the full-connection result.
The technical scheme realizes the classification operation of the AI classifier.
Optionally, the method may further include:
and the intelligent equipment sends the first class to the manual confirmation, receives a second class replied manually, and retrains and updates the AI classifier if the second class is different from the first class.
Referring to fig. 3, fig. 3 provides a terminal including:
the receiving and sending unit is used for receiving data sent by the industrial Internet;
the processing unit is used for inputting the data into the AI classifier to carry out classification operation to obtain a first class of the data; and performing hash operation on the data to obtain a first hash value, searching whether the first hash value exists in the first category, if so, adding a timestamp of the data in a note of the first hash value to receive a first command sent by the first terminal, and controlling an interface of the second terminal according to the first command.
An embodiment of the present invention further provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the FE industrial internet-based data classification methods described in the above method embodiments.
Embodiments of the present invention further provide a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute part or all of the steps of any of the FE industrial internet based data classification methods described in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules illustrated are not necessarily required to practice the invention.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may be implemented in the form of a software program module.
The integrated units, if implemented in the form of software program modules 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 invention may be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above embodiments of the present invention are described in detail, and the principle and the implementation of the present invention are explained by applying specific embodiments, and the above description of the embodiments is only used to help understanding the method of the present invention and the core idea thereof; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A data classification method based on an FE industrial internet is characterized by comprising the following steps:
the intelligent equipment receives data sent by the industrial Internet;
the intelligent equipment inputs the data into an AI classifier to carry out classification operation to obtain a first class of the data;
the intelligent device carries out hash operation on the data to obtain a first hash value, searches whether the first hash value exists in the first category, if so, adds a timestamp of the data in notes of the first hash value.
2. The method of claim 1, further comprising:
the intelligent device receives an extraction command of data, the extraction command comprises a time stamp, the intelligent device inquires a first hash value corresponding to the time stamp from a database of the first category, and data corresponding to the first hash value are extracted.
3. The method according to claim 1, wherein the intelligent device performing a classification operation on the data input into the AI classifier to obtain the first category of the data specifically comprises:
the intelligent device inputs the data serving as input data into the to-be-AI classifier to execute n layers of convolution operation to obtain a convolution operation result, executes full-connection operation on the convolution operation result to obtain a full-connection result, and determines the first category according to the full-connection result.
4. The method of claim 1, further comprising:
and the intelligent equipment sends the first class to the manual confirmation, receives a second class replied manually, and retrains and updates the AI classifier if the second class is different from the first class.
5. A terminal, characterized in that the terminal comprises:
the receiving and sending unit is used for receiving data sent by the industrial Internet;
the processing unit is used for inputting the data into the AI classifier to carry out classification operation to obtain a first class of the data; and performing hash operation on the data to obtain a first hash value, searching whether the first hash value exists in the first category, if so, adding a timestamp of the data in a note of the first hash value to receive a first command sent by the first terminal, and controlling an interface of the second terminal according to the first command.
6. The terminal of claim 5,
the receiving and sending unit is used for receiving an extraction command of data;
and the processing unit is used for inquiring a first hash value corresponding to the time stamp from the database of the first category and extracting data corresponding to the first hash value, wherein the extracting command contains the time stamp.
7. The terminal of claim 5,
the processing unit is specifically configured to input the data as input data into the to-be-AI classifier to perform n-layer convolution operation to obtain a convolution operation result, perform full-join operation on the convolution operation result to obtain a full-join result, and determine the first category according to the full-join result.
8. The terminal of claim 5,
the receiving and sending unit is also used for sending the first category to manual confirmation and receiving a second category of manual reply;
and the processing unit is used for retraining and updating the AI classifier if the second class is different from the first class.
9. A terminal according to any of claims 5-8,
the terminal is as follows: a smartphone, a tablet, a computer, or a server.
10. A computer-readable storage medium storing a program for electronic data exchange, wherein the program causes a terminal to perform the method as provided in any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201910722506.6A CN110597854A (en) | 2019-08-06 | 2019-08-06 | Data classification method based on FE industrial internet and related products |
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| CN201910722506.6A CN110597854A (en) | 2019-08-06 | 2019-08-06 | Data classification method based on FE industrial internet and related products |
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| CN110597854A true CN110597854A (en) | 2019-12-20 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111858783A (en) * | 2020-07-10 | 2020-10-30 | 脑谷人工智能研究院(南京)有限公司 | Data induction and arrangement platform based on big data intelligent analysis |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111858783A (en) * | 2020-07-10 | 2020-10-30 | 脑谷人工智能研究院(南京)有限公司 | Data induction and arrangement platform based on big data intelligent analysis |
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Application publication date: 20191220 |