CN113609359A - Garbage classification method, device, equipment and readable storage medium - Google Patents
Garbage classification method, device, equipment and readable storage medium Download PDFInfo
- Publication number
- CN113609359A CN113609359A CN202110875577.7A CN202110875577A CN113609359A CN 113609359 A CN113609359 A CN 113609359A CN 202110875577 A CN202110875577 A CN 202110875577A CN 113609359 A CN113609359 A CN 113609359A
- Authority
- CN
- China
- Prior art keywords
- garbage
- information
- classification
- user
- trained
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/906—Clustering; Classification
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a garbage classification method, a garbage classification device, garbage classification equipment and a readable storage medium, and relates to the technical field of artificial intelligence, wherein the method comprises the following steps: acquiring current city information; receiving text information or non-text information input by a user; when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage; and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result. The invention can realize automatic classification of garbage and has high accuracy.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a garbage classification method, a garbage classification device, garbage classification equipment and a readable storage medium.
Background
Garbage classification generally refers to a general term for a series of activities that store, release and transport garbage classified according to a certain rule or standard, thereby converting the garbage into a common resource. The classification aims to improve the resource value and the economic value of the garbage, strive for making the best use of things, reduce the garbage treatment capacity and the use of treatment equipment, reduce the treatment cost, reduce the consumption of land resources, and have social, economic, ecological and other benefits.
The main garbage classification methods at present are classified into manual and automatic. The automatic classification is mainly an automatic classification method based on image recognition. Due to the defects of image recognition, the recognition of objects with extremely similar filling materials, contents and partial appearances is difficult, and the garbage classification recognition is easy to be wrong.
Disclosure of Invention
The embodiment of the invention provides a garbage classification and grading method, which is used for realizing automatic classification of garbage and has high accuracy and comprises the following steps:
acquiring current city information;
receiving text information or non-text information input by a user;
when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage;
and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result.
The embodiment of the invention provides a garbage classification and grading device, which is used for realizing automatic classification of garbage and has high accuracy, and comprises:
the city information acquisition module is used for acquiring current city information;
the input receiving module is used for receiving character information or non-character information input by a user;
the keyword recognition module is used for inputting the non-character information into a pre-trained information recognition model and outputting the keywords of the garbage when the information input by the user is the non-character information;
and the garbage classification result obtaining module is used for inputting the current city information, the keyword of the garbage or the character information input by the user into a pre-trained garbage classification model to obtain a garbage classification result.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the above garbage classification method when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program for executing the above garbage classification method is stored in the computer-readable storage medium.
In the embodiment of the invention, the current city information is obtained; receiving text information or non-text information input by a user; when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage; and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result. The garbage classification method, the garbage classification device, the garbage classification equipment and the readable storage medium provided by the embodiment of the invention have the following beneficial effects that: for non-character information (such as voice information and picture information), based on the pre-trained information recognition model, the keyword of the garbage is output, then the keyword is combined with the city information and input into the pre-trained garbage classification model, a garbage classification result is obtained, and the efficiency and the precision of classification can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a flow chart of a garbage classification method according to an embodiment of the present invention;
FIG. 2 is a flowchart of obtaining a garbage classification result according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating the steps of training a garbage classification model according to an embodiment of the present invention;
FIG. 4 is a schematic view of a garbage classification apparatus according to an embodiment of the present invention;
FIG. 5 is another schematic view of the garbage classification apparatus according to the embodiment of the present invention;
FIG. 6 is a diagram of a computer device in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are used in an open-ended fashion, i.e., to mean including, but not limited to. Reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the embodiments is for illustrative purposes to illustrate the implementation of the present application, and the sequence of steps is not limited and can be adjusted as needed.
Fig. 1 is a flowchart of a garbage classification method in an embodiment of the present invention, and as shown in fig. 1, the method includes:
102, receiving character information or non-character information input by a user;
103, when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage;
and 104, inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result.
In the embodiment of the invention, for non-character information (such as voice information and picture information), the keyword of the garbage is output based on the pre-trained information recognition model, and then the keyword is combined with the city information and input into the pre-trained garbage classification model to obtain the garbage classification result, so that the classification efficiency and precision can be improved.
In step 101, current city information is obtained, and if the device implemented by the method is placed beside a trash can or in a user mobile phone, user positioning information can be obtained through trash can positioning, mobile phone positioning and the like, and then the current city information of the user is judged.
In step 102, receiving text information or non-text information input by a user, the device implementing the method can set an electronic screen, or borrow an electronic screen of equipment communicating with the device, including a keyboard output screen or a touch screen, and the like, and can accept the text information or the non-text information input by the user.
In one embodiment, the non-text information includes voice information and picture information;
the information recognition model comprises a voice recognition model and a picture recognition model.
That is, if the non-character information is voice information, such as "medicine bottle", "paint bucket", etc., the voice information is input to the pre-trained voice recognition model, and the keyword of the garbage is output, and if the non-character information is picture information, the picture information is input to the pre-trained picture recognition model, and the keyword of the garbage is output. The training mode of the voice recognition model and the picture recognition model is as follows: and training according to the labeled data set.
In an embodiment, the method further comprises:
when the non-character information is voice information and is a question provided by a user, inputting the obtained junk key words into a question-answer model to obtain an answer corresponding to the question;
and converting the answer into voice broadcast information.
In the above-described embodiment, the question is not limited to which classification the garbage belongs, and may ask what the garbage is, which classification it belongs to, why it belongs to, and the like.
The problem model includes:
a semantic analysis module to: performing semantic analysis on the problem;
a problem classification module to: obtaining a classification of the current problem based on semantic analysis;
a question keyword extraction module to: extracting keywords of the question based on the classification of the current question;
and the knowledge base automatic generation answer module is used for inquiring the knowledge base based on the key words of the questions to obtain corresponding answers.
In one embodiment, the garbage classification model comprises a garbage type classification model and a garbage disposal mode classification model;
fig. 2 is a flowchart of obtaining a garbage classification result in an embodiment of the present invention, where current city information, a keyword of the garbage, or text information input by a user is input into a pre-trained garbage classification model to obtain the garbage classification result, where the method includes:
Fig. 3 is a diagram of training steps of a garbage classification model in an embodiment of the present invention, in an embodiment, the training steps of the garbage classification model are as follows:
301, training a garbage type classification model according to a labeled garbage type data set to obtain a trained garbage type classification model;
In an embodiment, the labeled data set of garbage types includes a training set and a test set, the training set is used for training the garbage type classification model, and the test set is used for testing the trained garbage type classification model; the training set includes positive samples and negative samples.
In the above embodiment, positive samples are the correct garbage types and negative samples are the incorrect garbage types.
In an embodiment, the method further comprises:
and generating voice broadcast information based on the garbage classification result.
That is, whether the user inputs the text information or the non-text information, the text information or the non-text information can be played by voice.
In the method provided by the embodiment of the invention, the current city information is acquired; receiving text information or non-text information input by a user; when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage; and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result. In the process, for non-character information (such as voice information and picture information), the keyword of the garbage is output based on the pre-trained information recognition model, then the keyword is combined with the city information and input into the pre-trained garbage classification model to obtain a garbage classification result, and the efficiency and the precision of classification can be improved.
The embodiment of the invention also provides a garbage classification device, the principle of which is similar to that of a garbage classification method, and the detailed description is omitted here.
Fig. 4 is a schematic diagram of a garbage sorting apparatus according to an embodiment of the present invention, and as shown in fig. 4, the apparatus includes:
a city information obtaining module 401, configured to obtain current city information;
an input receiving module 402, configured to receive text information or non-text information input by a user;
a keyword recognition module 403, configured to, when information input by a user is non-text information, input the non-text information into a pre-trained information recognition model, and output a keyword of spam;
a garbage classification result obtaining module 404, configured to input the current city information, the keyword of the garbage, or the text information input by the user into a pre-trained garbage classification model, so as to obtain a garbage classification result.
In one embodiment, the non-text information includes voice information and picture information;
the information recognition model comprises a voice recognition model and a picture recognition model.
Fig. 5 is another schematic diagram of the garbage classification apparatus in an embodiment of the present invention, and in an embodiment, the apparatus further includes an intelligent question-answering module 405, configured to:
when the non-character information is voice information and is a question provided by a user, inputting the obtained junk key words into a question-answer model to obtain an answer corresponding to the question;
and converting the answer into voice broadcast information.
In one embodiment, the garbage classification model comprises a garbage type classification model and a garbage disposal mode classification model;
the garbage classification result obtaining module is specifically configured to:
inputting the keyword of the garbage or the character information input by the user into a garbage type classification model trained in advance to obtain the type of the garbage;
and inputting the current city information, the keywords of the garbage or the character information input by the user into a garbage disposal mode classification model trained in advance to obtain garbage disposal mode classification.
In one embodiment, the training of the garbage classification model comprises the following steps:
training a garbage type classification model according to the labeled garbage type data set to obtain a trained garbage type classification model;
and inputting the output data of the trained garbage type classification model, the labeled garbage disposal mode data set and the labeled city information into the garbage disposal mode classification model for training to obtain the trained garbage disposal mode classification model.
In an embodiment, the labeled data set of garbage types includes a training set and a test set, the training set is used for training the garbage type classification model, and the test set is used for testing the trained garbage type classification model; the training set includes positive samples and negative samples.
In an embodiment, the apparatus further includes a broadcast module 406, configured to:
and generating voice broadcast information based on the garbage classification result.
In summary, in the apparatus provided in the embodiment of the present invention, the current city information is obtained; receiving text information or non-text information input by a user; when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage; and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result. In the process, for non-character information (such as voice information and picture information), the keyword of the garbage is output based on the pre-trained information recognition model, then the keyword is combined with the city information and input into the pre-trained garbage classification model to obtain a garbage classification result, and the efficiency and the precision of classification can be improved.
An embodiment of the present application further provides a computer device, and fig. 6 is a schematic diagram of the computer device in the embodiment of the present invention, where the computer device is capable of implementing all steps in the garbage classification method in the embodiment, and includes:
acquiring current city information;
receiving text information or non-text information input by a user;
when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage;
and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result.
The computer device specifically comprises the following contents:
a processor (processor)601, a memory (memory)602, a communication Interface (Communications Interface)603, and a communication bus 604;
the processor 601, the memory 602 and the communication interface 603 complete mutual communication through the communication bus 604; the communication interface 603 is used for implementing information transmission among related devices such as server-side devices, detection devices, user-side devices and the like;
the processor 601 is configured to call a computer program in the memory 602, and when the processor executes the computer program, the processor implements all the steps of the garbage classification method in the above embodiments.
An embodiment of the present application further provides a computer-readable storage medium, which can implement all the steps in the garbage classification method in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements all the steps of the garbage classification method in the foregoing embodiment, and the method includes:
acquiring current city information;
receiving text information or non-text information input by a user;
when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage;
and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may 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, and the like) having computer-usable program code embodied therein.
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 will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (13)
1. A method of sorting waste, comprising:
acquiring current city information;
receiving text information or non-text information input by a user;
when the information input by the user is non-character information, inputting the non-character information into a pre-trained information recognition model, and outputting the keywords of the garbage;
and inputting the current city information, the keyword of the garbage or the character information input by the user into a garbage classification model trained in advance to obtain a garbage classification result.
2. The method of garbage classification of claim 1 wherein the non-textual information includes voice information and picture information;
the information recognition model comprises a voice recognition model and a picture recognition model.
3. The method of sorting refuse according to claim 2, further comprising:
when the non-character information is voice information and is a question provided by a user, inputting the obtained junk key words into a question-answer model to obtain an answer corresponding to the question;
and converting the answer into voice broadcast information.
4. The garbage classification method of claim 1, wherein the garbage classification model comprises a garbage type classification model and a garbage disposal mode classification model;
inputting the current city information, the keyword of the garbage or the text information input by the user into a garbage classification model trained in advance to obtain a garbage classification result, wherein the garbage classification result comprises the following steps:
inputting the keyword of the garbage or the character information input by the user into a garbage type classification model trained in advance to obtain the type of the garbage;
and inputting the current city information, the keywords of the garbage or the character information input by the user into a garbage disposal mode classification model trained in advance to obtain garbage disposal mode classification.
5. The garbage classification method of claim 4, wherein the training of the garbage classification model comprises the steps of:
training a garbage type classification model according to the labeled garbage type data set to obtain a trained garbage type classification model;
and inputting the output data of the trained garbage type classification model, the labeled garbage disposal mode data set and the labeled city information into the garbage disposal mode classification model for training to obtain the trained garbage disposal mode classification model.
6. The garbage classification method of claim 5 wherein the labeled garbage type data set comprises a training set and a test set, the training set is used for training the garbage type classification model, and the test set is used for testing the trained garbage type classification model; the training set includes positive samples and negative samples.
7. The method of sorting garbage according to claim 1, further comprising:
and generating voice broadcast information based on the garbage classification result.
8. A waste sorting device, comprising:
the city information acquisition module is used for acquiring current city information;
the input receiving module is used for receiving character information or non-character information input by a user;
the keyword recognition module is used for inputting the non-character information into a pre-trained information recognition model and outputting the keywords of the garbage when the information input by the user is the non-character information;
and the garbage classification result obtaining module is used for inputting the current city information, the keyword of the garbage or the character information input by the user into a pre-trained garbage classification model to obtain a garbage classification result.
9. The garbage classification apparatus of claim 8 wherein the non-textual information includes voice information and picture information;
the information recognition model comprises a voice recognition model and a picture recognition model.
10. The garbage classification device of claim 9, further comprising an intelligent question-and-answer module to:
when the non-character information is voice information and is a question provided by a user, inputting the obtained junk key words into a question-answer model to obtain an answer corresponding to the question;
and converting the answer into voice broadcast information.
11. The waste sorting device of claim 8, further comprising a broadcast module configured to:
and generating voice broadcast information based on the garbage classification result.
12. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 7 when executing the computer program.
13. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110875577.7A CN113609359A (en) | 2021-07-30 | 2021-07-30 | Garbage classification method, device, equipment and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110875577.7A CN113609359A (en) | 2021-07-30 | 2021-07-30 | Garbage classification method, device, equipment and readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113609359A true CN113609359A (en) | 2021-11-05 |
Family
ID=78306303
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110875577.7A Pending CN113609359A (en) | 2021-07-30 | 2021-07-30 | Garbage classification method, device, equipment and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113609359A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110428817A (en) * | 2019-08-06 | 2019-11-08 | 上海上班族电子商务有限公司 | A kind of garbage classification speech recognition system based on artificial intelligence |
| CN110458193A (en) * | 2019-07-08 | 2019-11-15 | 北京百度网讯科技有限公司 | Garbage classification processing method, apparatus and system, computer equipment and readable medium |
| CN110569874A (en) * | 2019-08-05 | 2019-12-13 | 深圳大学 | Garbage classification method and device, intelligent terminal and storage medium |
| CN111310071A (en) * | 2020-01-17 | 2020-06-19 | 苏州思必驰信息科技有限公司 | Garbage classification method, device, equipment and storage medium |
| CN112492606A (en) * | 2020-11-10 | 2021-03-12 | 恒安嘉新（北京）科技股份公司 | Classification and identification method and device for spam messages, computer equipment and storage medium |
-
2021
- 2021-07-30 CN CN202110875577.7A patent/CN113609359A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110458193A (en) * | 2019-07-08 | 2019-11-15 | 北京百度网讯科技有限公司 | Garbage classification processing method, apparatus and system, computer equipment and readable medium |
| CN110569874A (en) * | 2019-08-05 | 2019-12-13 | 深圳大学 | Garbage classification method and device, intelligent terminal and storage medium |
| CN110428817A (en) * | 2019-08-06 | 2019-11-08 | 上海上班族电子商务有限公司 | A kind of garbage classification speech recognition system based on artificial intelligence |
| CN111310071A (en) * | 2020-01-17 | 2020-06-19 | 苏州思必驰信息科技有限公司 | Garbage classification method, device, equipment and storage medium |
| CN112492606A (en) * | 2020-11-10 | 2021-03-12 | 恒安嘉新（北京）科技股份公司 | Classification and identification method and device for spam messages, computer equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108595696A (en) | A kind of human-computer interaction intelligent answering method and system based on cloud platform | |
| CN107506346A (en) | A kind of Chinese reading grade of difficulty method and system based on machine learning | |
| CN108334493B (en) | Question knowledge point automatic extraction method based on neural network | |
| CN109325040B (en) | FAQ question-answer library generalization method, device and equipment | |
| CN107766371A (en) | A kind of text message sorting technique and its device | |
| CN105224665A (en) | A kind of wrong topic management method and system | |
| KR102259390B1 (en) | System and method for ensemble question-answering | |
| CN109408821B (en) | Corpus generation method and device, computing equipment and storage medium | |
| CN106503074B (en) | Topic refining and classifying method | |
| CN110910283A (en) | Method, device, equipment and storage medium for generating legal document | |
| CN105912527A (en) | Method, device and system outputting answer according to natural language | |
| CN110097094A (en) | It is a kind of towards personage interaction multiple semantic fusion lack sample classification method | |
| CN116483982B (en) | Knowledge question-answering method, knowledge question-answering device, electronic equipment and readable storage medium | |
| CN111159356B (en) | Knowledge graph construction method based on teaching content | |
| CN109635080A (en) | Acknowledgment strategy generation method and device | |
| CN105930490A (en) | Intelligent selecting system for teaching resources | |
| CN103885933A (en) | Method and equipment for evaluating text sentiment | |
| CN101470699B (en) | Information extraction model training apparatus, information extraction apparatus and information extraction system and method thereof | |
| CN116719957B (en) | Learning content distribution method and system based on portrait mining | |
| CN113609359A (en) | Garbage classification method, device, equipment and readable storage medium | |
| CN110750632B (en) | Improved Chinese ALICE intelligent question-answering method and system | |
| CN114491010A (en) | Training method and device of information extraction model | |
| CN113221577A (en) | Education text knowledge induction method, system, equipment and readable storage medium | |
| CN111860083A (en) | Character relation completion method and device | |
| CN111930959A (en) | Method and device for generating text by using map knowledge |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |