SG11201906380PA - Data type recognition, model training and risk recognition methods, apparatuses and devices - Google Patents
Data type recognition, model training and risk recognition methods, apparatuses and devicesInfo
- Publication number
- SG11201906380PA SG11201906380PA SG11201906380PA SG11201906380PA SG11201906380PA SG 11201906380P A SG11201906380P A SG 11201906380PA SG 11201906380P A SG11201906380P A SG 11201906380PA SG 11201906380P A SG11201906380P A SG 11201906380PA SG 11201906380P A SG11201906380P A SG 11201906380PA
- Authority
- SG
- Singapore
- Prior art keywords
- model
- recognition
- data
- sample data
- data set
- Prior art date
Links
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/55—Detecting local intrusion or implementing counter-measures
- G06F21/552—Detecting local intrusion or implementing counter-measures involving long-term monitoring or reporting
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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
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/03—Indexing scheme relating to G06F21/50, monitoring users, programs or devices to maintain the integrity of platforms
- G06F2221/034—Test or assess a computer or a system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computing arrangements based on specific mathematical models
- G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Entrepreneurship & Innovation (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Mathematical Physics (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Computer Security & Cryptography (AREA)
- Development Economics (AREA)
- Fuzzy Systems (AREA)
- Educational Administration (AREA)
- Computational Linguistics (AREA)
- Game Theory and Decision Science (AREA)
- Probability & Statistics with Applications (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Evolutionary Biology (AREA)
- Computer Hardware Design (AREA)
- Medical Informatics (AREA)
- Computing Systems (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Image Analysis (AREA)
Abstract
The present application provides data type recognition and model training methods and apparatuses, and computer devices. The model training method includes acquiring a first sample data set, and using the first sample data set to train an anomaly detection model; and detecting an abnormal sample data set from a second sample data set by means of the 5 anomaly detection model, and using the abnormal sample data set to train a classification model. By means of this embodiment, an amount of scoring events of the classification model can be reduced, and relatively balanced sample data sets can also be provided for training, to obtain the classification model with a higher accuracy. In a particular application, data to be recognized is firstly input to the anomaly detection model, and whether the data 10 to be recognized is first-type data can be quickly distinguished; and other data than the first- type data recognized by the anomaly detection model, is input to the classification model for recognition. The speed of online data recognition is relatively fast.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710458652.3A CN107391569B (en) | 2017-06-16 | 2017-06-16 | Data type identification, model training and risk identification method, device and equipment |
PCT/CN2018/091043 WO2018228428A1 (en) | 2017-06-16 | 2018-06-13 | Data type identification, model training, and risk identification method and apparatus, and device |
Publications (1)
Publication Number | Publication Date |
---|---|
SG11201906380PA true SG11201906380PA (en) | 2019-08-27 |
Family
ID=60333026
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
SG11201906380PA SG11201906380PA (en) | 2017-06-16 | 2018-06-13 | Data type recognition, model training and risk recognition methods, apparatuses and devices |
Country Status (7)
Country | Link |
---|---|
US (2) | US11113394B2 (en) |
CN (1) | CN107391569B (en) |
MY (1) | MY201302A (en) |
PH (1) | PH12019501621A1 (en) |
SG (1) | SG11201906380PA (en) |
TW (1) | TWI664535B (en) |
WO (1) | WO2018228428A1 (en) |
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-
2017
- 2017-06-16 CN CN201710458652.3A patent/CN107391569B/en active Active
-
2018
- 2018-03-14 TW TW107108576A patent/TWI664535B/en active
- 2018-06-13 SG SG11201906380PA patent/SG11201906380PA/en unknown
- 2018-06-13 WO PCT/CN2018/091043 patent/WO2018228428A1/en active Application Filing
- 2018-06-13 MY MYPI2019003977A patent/MY201302A/en unknown
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2019
- 2019-06-18 US US16/444,156 patent/US11113394B2/en active Active
- 2019-07-11 PH PH12019501621A patent/PH12019501621A1/en unknown
-
2020
- 2020-01-28 US US16/774,663 patent/US11100220B2/en active Active
Also Published As
Publication number | Publication date |
---|---|
MY201302A (en) | 2024-02-15 |
TWI664535B (en) | 2019-07-01 |
CN107391569B (en) | 2020-09-15 |
TW201905728A (en) | 2019-02-01 |
US11100220B2 (en) | 2021-08-24 |
CN107391569A (en) | 2017-11-24 |
WO2018228428A1 (en) | 2018-12-20 |
US11113394B2 (en) | 2021-09-07 |
US20190303569A1 (en) | 2019-10-03 |
PH12019501621A1 (en) | 2020-01-20 |
US20200167466A1 (en) | 2020-05-28 |
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