CN114092254A - Consumption financial transaction method based on artificial intelligence and transaction system thereof - Google Patents
Consumption financial transaction method based on artificial intelligence and transaction system thereof Download PDFInfo
- Publication number
- CN114092254A CN114092254A CN202111420631.5A CN202111420631A CN114092254A CN 114092254 A CN114092254 A CN 114092254A CN 202111420631 A CN202111420631 A CN 202111420631A CN 114092254 A CN114092254 A CN 114092254A
- Authority
- CN
- China
- Prior art keywords
- data
- transaction
- module
- information
- model
- 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
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/211—Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Finance (AREA)
- General Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Artificial Intelligence (AREA)
- Accounting & Taxation (AREA)
- Health & Medical Sciences (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Machine Translation (AREA)
Abstract
The invention discloses a consumption financial transaction method and a transaction system based on artificial intelligence, wherein the method comprises the following steps: the system comprises a data acquisition module, a data processing module, a data analysis module, a model construction module, a model inspection module, a model training module, a transaction sending module, a data storage module and a system optimization module; the invention applies artificial intelligence to financial transaction, improves the data acquisition and processing efficiency, solves the problem of limited data processing capacity of the traditional transaction method, can effectively collect and extract financial data information, establishes a relevant prediction model and makes transaction decisions, so that the transaction is not interfered by human factors, and in addition, the system can be stopped in time when decision errors occur by monitoring the transaction process in real time, thereby ensuring the transaction safety.
Description
Technical Field
The invention relates to the technical field of electronic transaction, in particular to a consumption financial transaction method based on artificial intelligence and a transaction system thereof.
Background
The financial transaction refers to all transactions involving ownership change of financial assets of an institution unit, including generation and settlement of financial debt rights and liabilities, in the financial transaction, one institution unit can form or dispose of the financial assets on one hand, and offset the net acquisition of the financial assets in the future; on the other hand, debt can be generated and cleared, and the net occurrence of debt is reflected later, the essence of finance is that capital value is configured across space and time, all value-related transactions across space and time belong to financial transactions, and the basic situation in the field of domestic financial transactions at present is as follows: the commercial bank not only keeps the counter transaction of the network, but also contributes to the platform on the operation line; the internet finance is developed to construct a platform based on the technologies of internet, cloud computing, data transmission and the like to facilitate the transaction of customers, so that the transaction is carried out on line.
At present, in the process of financial transaction, human factors can influence the accuracy of transaction decision, mainly because human weaknesses and physiological limits can lead the transaction decision to be hesitant, thereby leading the transaction to be uncertain, and further influencing the financial transaction process, and because the data processing capacity of the traditional computer is limited, only structured data can be processed, thereby influencing the accuracy of model prediction in the financial transaction process.
Disclosure of Invention
The invention aims to provide an artificial intelligence based consumption financial transaction method and a transaction system thereof, wherein the method utilizes an artificial intelligence computer vision technology, a voice recognition technology and a natural language processing technology to collect and process unstructured data of financial transactions, improves the data collection and processing efficiency, applies the artificial intelligence to the financial transactions, can effectively collect and extract financial data information, establishes a relevant prediction model and makes transaction decisions, so that the transactions are not interfered by human factors, the uncertainty in the transaction process is eliminated, the system has strong working stability, the smooth transaction process is ensured, and the transaction decisions and the execution are independent.
In order to achieve the purpose of the invention, the invention is realized by the following technical scheme: an artificial intelligence based consumption financial transaction method, comprising the steps of:
the method comprises the following steps: firstly, acquiring structured data information of financial transactions from a public data end of a financial market, then collecting unstructured data information of the financial transactions by combining a computer vision technology and a voice recognition technology, and then carrying out noise reduction processing on the unstructured data by utilizing a natural language processing technology to obtain structured information for systematic understanding;
step two: analyzing acquired structured data information and processed structured information by using a machine learning technology, constructing a data speculation model by combining historical transaction data and an analysis result, checking whether the data speculation model has a logic error by using a knowledge graph, performing logic perfection on the data speculation model if the data speculation model has the logic error, and entering a subsequent step if the data speculation model has the logic error;
step three: the method comprises the steps of firstly, carrying out cyclic training on a data speculation model without logic errors by utilizing a deep learning technology to automatically optimize the data speculation model and obtain a prediction model which is in line with the reality and is adaptive to market environment changes, then carrying out prediction analysis and judgment on the change of market financial transaction data through the prediction model to obtain an investment decision of financial transaction, sending a transaction instruction to the market according to the investment decision and waiting for market reply, carrying out real-time monitoring on the transaction process after the transaction instruction is sent out by a system, carrying out auxiliary supervision through manpower in the real-time monitoring process, and stopping the system in time when the system has errors;
step four: after the transaction instruction is sent out, data storage is carried out on all the sent transaction instructions through the data storage module, the stored data are analyzed after the transaction is finished, and the system is perfected according to the analysis result.
The further improvement lies in that: in the first step, the structured data information includes market data and quotation information, and the unstructured data information includes market research reports and national news policies.
The further improvement lies in that: in the first step, the step of collecting unstructured data information by using a computer vision technology specifically comprises the following steps: firstly, collecting image information, then detecting a target in the image information, segmenting the target information and background information, then cutting off the background information and reserving the target information, and finally identifying actually required unstructured data information according to the target information.
The further improvement lies in that: in the first step, the collecting of the unstructured data information by using the voice recognition technology specifically comprises: firstly, voice information is collected, then the collected voice information is converted into a text format, and finally the actually needed unstructured data information is identified according to the converted text format.
The further improvement lies in that: in the first step, the analyzing and processing the unstructured data by using the natural language processing period number specifically comprises: the method comprises the steps of splitting a sentence into words through a lexical analysis technology, determining the meaning of the words, analyzing the vocabulary phrases through the syntactic analysis technology, identifying a syntactic structure, combining the split words through a semantic analysis technology, understanding the meaning of the sentence, and obtaining structural information for systematic understanding.
The further improvement lies in that: in the third step, if the market reply content is order bargain, the system predicts the financial transaction information of the future market according to the order bargain result, and if the market reply content is order non-bargain, the system withdraws the transaction instruction and further analyzes the investment decision.
The transaction system comprises a data acquisition module, a data processing module, a data analysis module, a model building module, a model checking module, a model training module, a transaction sending module, a data storage module and a system optimization module, wherein the data acquisition module is connected with the data analysis module through the data processing module, the data analysis module is connected with the model checking module through the model building module, the model checking module is connected with the transaction sending module through the model training module, the transaction sending module is connected with the system optimization module through the data storage module, the model checking module is further connected with a logic perfecting module, and the transaction sending module is further connected with a transaction supervision module.
The further improvement lies in that: the data acquisition module comprises a structured data acquisition unit and an unstructured data acquisition unit, the structured data acquisition unit is used for acquiring structured data information of financial transactions, and the unstructured data acquisition unit is used for acquiring unstructured data information of the financial transactions.
The invention has the beneficial effects that: the invention utilizes the computer vision technology, the voice recognition technology and the natural language processing technology of artificial intelligence to collect and process the unstructured data of financial transactions, improves the data collection and processing efficiency, solves the problem of limited data processing capability of the traditional transaction method, applies the artificial intelligence to the financial transactions, can effectively collect and extract the financial data information, establish a relevant prediction model and make transaction decisions, ensures that the transactions are not interfered by human factors, eliminates uncertainty generated in the transaction process, ensures that the system has stronger working stability, ensures the smooth proceeding of the transaction process, ensures that the transaction decisions and execution are independent, thereby leading mass financial transaction data to be quickly analyzed, fitted and judged, and the deep learning technology trains the data speculation model, leading the system to independently learn historical and real-time transaction data, and moreover, the system can be stopped in time when a decision error occurs through real-time monitoring of the trading process, so that the trading safety is ensured.
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, and 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 these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram of a system according to a second 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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Example one
Referring to fig. 1, the present embodiment provides an artificial intelligence based consumption financial transaction method, including the following steps:
the method comprises the following steps: firstly, acquiring structured data information of financial transactions from a public data end of a financial market, wherein the structured data information comprises market data and quotation information, acquiring unstructured data information of the financial transactions, including market research reports and national news policies, by combining a computer vision technology and a voice recognition technology, then performing noise reduction processing on the unstructured data by using a natural language processing technology, and obtaining structured information for system understanding;
the method for acquiring the unstructured data information by using the computer vision technology specifically comprises the following steps: firstly, collecting image information, then detecting a target in the image information, segmenting the target information and background information, then cutting off the background information and reserving the target information, and finally identifying actually required unstructured data information according to the target information;
the method for acquiring the unstructured data information by utilizing the voice recognition technology specifically comprises the following steps: firstly, voice information is collected, then the collected voice information is converted into a text format, and then the actually required unstructured data information is identified according to the converted text format;
the analyzing and processing of the unstructured data by using the natural language processing period number specifically comprises the following steps: firstly, splitting a sentence into words by a lexical analysis technology, determining the meaning of the words, analyzing the vocabulary phrases by the syntactic analysis technology, identifying the syntactic structure, and finally, combining the split words by the semantic analysis technology and understanding the meaning of the sentence to obtain the structural information for systematic understanding
Step two: analyzing acquired structured data information and processed structured information by using a machine learning technology, constructing a data speculation model by combining historical transaction data and an analysis result, checking whether the data speculation model has a logic error by using a knowledge graph, performing logic perfection on the data speculation model if the data speculation model has the logic error, and performing subsequent steps if the data speculation model has the logic error;
step three: firstly, a deep learning technology is utilized to carry out cycle training on the data speculation model without logic errors, the model is presumed by automatically optimizing the data, and a prediction model which accords with the reality and adapts to the market environment change is obtained, then, the change of the market financial transaction data is predicted, analyzed and judged through a prediction model to obtain an investment decision of the financial transaction, a transaction instruction is sent to the market according to the investment decision and the market is waited to reply, if the market reply content is order bargain, the system predicts the financial transaction information of the future market according to the order transaction result, if the market reply content is that the order is not committed, the system withdraws the transaction instruction and further analyzes the investment decision, the system monitors the transaction process in real time after sending the transaction instruction, performs auxiliary supervision through manpower in the real-time monitoring process, and stops the system in time when the system has errors;
step four: after the transaction instruction is sent out, data storage is carried out on all the sent transaction instructions through the data storage module, the stored data are analyzed after the transaction is finished, and the system is perfected according to the analysis result.
Example two
Referring to fig. 2, the embodiment provides a transaction system of a consumption financial transaction method based on artificial intelligence, which includes a data acquisition module for acquiring financial transaction data, a data processing module for performing noise reduction processing on unstructured data, a data analysis module for analyzing the acquired data, a model construction module for establishing a data speculation model, a model verification module for verifying a logic error of the data speculation model, a model training module for training and optimizing the data speculation model, a transaction issue module for issuing a transaction instruction according to a transaction decision, a data storage module for storing the transaction data, and a system optimization module for optimizing the system, wherein the data acquisition module is connected with the data analysis module through the data processing module, the data analysis module is connected with the model verification module through the model construction module, the model checking module is connected with the transaction sending module through the model training module, the transaction sending module is connected with the system optimization module through the data storage module, the model checking module is further connected with a logic perfecting module for performing logic perfection on the data speculation model, and the transaction sending module is further connected with a transaction monitoring module for performing real-time monitoring on the transaction process.
The data acquisition module comprises a structured data acquisition unit and an unstructured data acquisition unit, the structured data acquisition unit is used for acquiring structured data information of financial transactions, and the unstructured data acquisition unit is used for acquiring unstructured data information of the financial transactions.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A consumption financial transaction method based on artificial intelligence is characterized by comprising the following steps:
the method comprises the following steps: firstly, acquiring structured data information of financial transactions from a public data end of a financial market, then collecting unstructured data information of the financial transactions by combining a computer vision technology and a voice recognition technology, and then carrying out noise reduction processing on the unstructured data by utilizing a natural language processing technology to obtain structured information for systematic understanding;
step two: analyzing acquired structured data information and processed structured information by using a machine learning technology, constructing a data speculation model by combining historical transaction data and an analysis result, checking whether the data speculation model has a logic error by using a knowledge graph, performing logic perfection on the data speculation model if the data speculation model has the logic error, and entering a subsequent step if the data speculation model has the logic error;
step three: the method comprises the steps of firstly, carrying out cyclic training on a data speculation model without logic errors by utilizing a deep learning technology to automatically optimize the data speculation model and obtain a prediction model which is in line with the reality and is adaptive to market environment changes, then carrying out prediction analysis and judgment on the change of market financial transaction data through the prediction model to obtain an investment decision of financial transaction, sending a transaction instruction to the market according to the investment decision and waiting for market reply, carrying out real-time monitoring on the transaction process after the transaction instruction is sent out by a system, carrying out auxiliary supervision through manpower in the real-time monitoring process, and stopping the system in time when the system has errors;
step four: after the transaction instruction is sent out, data storage is carried out on all the sent transaction instructions through the data storage module, the stored data are analyzed after the transaction is finished, and the system is perfected according to the analysis result.
2. The artificial intelligence based consuming financial transaction method of claim 1, wherein: in the first step, the structured data information includes market data and quotation information, and the unstructured data information includes market research reports and national news policies.
3. The artificial intelligence based consuming financial transaction method of claim 1, wherein: in the first step, the step of collecting unstructured data information by using a computer vision technology specifically comprises the following steps: firstly, collecting image information, then detecting a target in the image information, segmenting the target information and background information, then cutting off the background information and reserving the target information, and finally identifying actually required unstructured data information according to the target information.
4. The artificial intelligence based consuming financial transaction method of claim 1, wherein: in the first step, the collecting of the unstructured data information by using the voice recognition technology specifically comprises: firstly, voice information is collected, then the collected voice information is converted into a text format, and finally the actually needed unstructured data information is identified according to the converted text format.
5. The artificial intelligence based consuming financial transaction method of claim 1, wherein: in the first step, the analyzing and processing the unstructured data by using the natural language processing period number specifically comprises: the method comprises the steps of splitting a sentence into words through a lexical analysis technology, determining the meaning of the words, analyzing the vocabulary phrases through the syntactic analysis technology, identifying a syntactic structure, combining the split words through a semantic analysis technology, understanding the meaning of the sentence, and obtaining structural information for systematic understanding.
6. The artificial intelligence based consuming financial transaction method of claim 1, wherein: in the third step, if the market reply content is order bargain, the system predicts the financial transaction information of the future market according to the order bargain result, and if the market reply content is order non-bargain, the system withdraws the transaction instruction and further analyzes the investment decision.
7. A transaction system of a consumption financial transaction method based on artificial intelligence is characterized in that: the system comprises a data acquisition module, a data processing module, a data analysis module, a model construction module, a model inspection module, a model training module, a transaction sending module, a data storage module and a system optimization module, wherein the data acquisition module is connected with the data analysis module through the data processing module, the data analysis module is connected with the model inspection module through the model construction module, the model inspection module is connected with the transaction sending module through the model training module, the transaction sending module is connected with the system optimization module through the data storage module, the model inspection module is further connected with a logic perfection module, and the transaction sending module is further connected with a transaction supervision module.
8. The transaction system of claim 7, wherein the transaction system comprises: the data acquisition module comprises a structured data acquisition unit and an unstructured data acquisition unit, the structured data acquisition unit is used for acquiring structured data information of financial transactions, and the unstructured data acquisition unit is used for acquiring unstructured data information of the financial transactions.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111420631.5A CN114092254A (en) | 2021-11-26 | 2021-11-26 | Consumption financial transaction method based on artificial intelligence and transaction system thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111420631.5A CN114092254A (en) | 2021-11-26 | 2021-11-26 | Consumption financial transaction method based on artificial intelligence and transaction system thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114092254A true CN114092254A (en) | 2022-02-25 |
Family
ID=80304970
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111420631.5A Pending CN114092254A (en) | 2021-11-26 | 2021-11-26 | Consumption financial transaction method based on artificial intelligence and transaction system thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114092254A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114648337A (en) * | 2022-03-23 | 2022-06-21 | 中银金融科技有限公司 | Transaction data quality automatic analysis method and device |
| CN114942985A (en) * | 2022-06-08 | 2022-08-26 | 广州芸荟数字软件有限公司 | Artificial intelligence data processing method and system based on machine learning |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150227935A1 (en) * | 2015-02-28 | 2015-08-13 | Brighterion, Inc. | Payment authorization data processing system for optimizing profits otherwise lost in false positives |
| CN110335162A (en) * | 2019-07-18 | 2019-10-15 | 电子科技大学 | A kind of stock market quantization transaction system and algorithm based on deeply study |
| CN111291925A (en) * | 2020-01-18 | 2020-06-16 | 武汉盛信鸿通科技有限公司 | Financial market prediction and decision-making system and method based on artificial intelligence |
| CN111882438A (en) * | 2020-08-12 | 2020-11-03 | 上海非凸智能科技有限公司 | Intelligent algorithm transaction method |
| CN112233343A (en) * | 2020-10-19 | 2021-01-15 | 中国工商银行股份有限公司 | Self-service terminal equipment service data processing method and device |
| CN112418575A (en) * | 2019-08-22 | 2021-02-26 | 刘畅 | Futures initiative contract quantitative timing decision system based on cloud computing and artificial intelligence deep learning algorithm |
-
2021
- 2021-11-26 CN CN202111420631.5A patent/CN114092254A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150227935A1 (en) * | 2015-02-28 | 2015-08-13 | Brighterion, Inc. | Payment authorization data processing system for optimizing profits otherwise lost in false positives |
| CN110335162A (en) * | 2019-07-18 | 2019-10-15 | 电子科技大学 | A kind of stock market quantization transaction system and algorithm based on deeply study |
| CN112418575A (en) * | 2019-08-22 | 2021-02-26 | 刘畅 | Futures initiative contract quantitative timing decision system based on cloud computing and artificial intelligence deep learning algorithm |
| CN111291925A (en) * | 2020-01-18 | 2020-06-16 | 武汉盛信鸿通科技有限公司 | Financial market prediction and decision-making system and method based on artificial intelligence |
| CN111882438A (en) * | 2020-08-12 | 2020-11-03 | 上海非凸智能科技有限公司 | Intelligent algorithm transaction method |
| CN112233343A (en) * | 2020-10-19 | 2021-01-15 | 中国工商银行股份有限公司 | Self-service terminal equipment service data processing method and device |
Non-Patent Citations (1)
| Title |
|---|
| 肖京等: "感知认知技术在金融风险预警中的应用研究", 《感知认知技术在金融风险预警中的应用研究》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114648337A (en) * | 2022-03-23 | 2022-06-21 | 中银金融科技有限公司 | Transaction data quality automatic analysis method and device |
| CN114942985A (en) * | 2022-06-08 | 2022-08-26 | 广州芸荟数字软件有限公司 | Artificial intelligence data processing method and system based on machine learning |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110096570B (en) | Intention identification method and device applied to intelligent customer service robot | |
| CN114092254A (en) | Consumption financial transaction method based on artificial intelligence and transaction system thereof | |
| CN108829682B (en) | Computer readable storage medium, intelligent question answering method and intelligent question answering device | |
| CN111859969B (en) | Data analysis method and device, electronic equipment and storage medium | |
| CN112967144B (en) | Financial credit risk event extraction method, readable storage medium and device | |
| CN112183059B (en) | Chinese structured event extraction method | |
| CN111966796A (en) | Question and answer pair extraction method, device and equipment and readable storage medium | |
| JP2018198045A (en) | Apparatus and method for generation of natural language processing event | |
| CN112541070A (en) | Method and device for excavating slot position updating corpus, electronic equipment and storage medium | |
| CN111738018A (en) | Intention understanding method, device, equipment and storage medium | |
| CN112016327A (en) | Intelligent structured text extraction method and device based on multiple rounds of conversations and electronic equipment | |
| CN114202243A (en) | Engineering project management risk early warning method and system based on random forest | |
| CN116150613A (en) | Information extraction model training method, information extraction method and device | |
| CN117251559B (en) | Engineering standard specification acquisition method and system based on natural language big model | |
| CN116992847A (en) | Financial report processing method, device, system and medium | |
| CN110796565A (en) | Analysis method and analysis system for supervision logs | |
| CN114461665B (en) | Method, apparatus and computer program product for generating a statement transformation model | |
| CN116842143A (en) | Dialog simulation method and device based on artificial intelligence, electronic equipment and medium | |
| CN113033179B (en) | Knowledge acquisition method, knowledge acquisition device, electronic equipment and readable storage medium | |
| CN114138743A (en) | ETL task automatic configuration method and device based on machine learning | |
| CN114064904A (en) | Clustering method, system and device for medical texts | |
| CN111427880A (en) | Data processing method, device, computing equipment and medium | |
| CN112818972A (en) | Method and device for detecting interest point image, electronic equipment and storage medium | |
| Huang et al. | Text analysis of power customer complaint work order based on data mining | |
| CN111709669A (en) | Enterprise credit scoring system and method |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20220225 |