CN117677959A - 使用经训练的机器学习管线识别分类层次结构 - Google Patents
使用经训练的机器学习管线识别分类层次结构 Download PDFInfo
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- CN117677959A CN117677959A CN202280049145.3A CN202280049145A CN117677959A CN 117677959 A CN117677959 A CN 117677959A CN 202280049145 A CN202280049145 A CN 202280049145A CN 117677959 A CN117677959 A CN 117677959A
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- classification
- machine learning
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/3332—Query translation
- G06F16/3335—Syntactic pre-processing, e.g. stopword elimination, stemming
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3347—Query execution using vector based model
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
- G06F18/231—Hierarchical techniques, i.e. dividing or merging pattern sets so as to obtain a dendrogram
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0499—Feedforward networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/751—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Mathematical Physics (AREA)
- Databases & Information Systems (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Medical Informatics (AREA)
- Multimedia (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US17/303,918 US20220398445A1 (en) | 2021-06-10 | 2021-06-10 | Identifying a classification hierarchy using a trained machine learning pipeline |
| US17/303,918 | 2021-06-10 | ||
| PCT/US2022/032705 WO2022261233A1 (en) | 2021-06-10 | 2022-06-08 | Identifying a classification hierarchy using a trained machine learning pipeline |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117677959A true CN117677959A (zh) | 2024-03-08 |
Family
ID=82482578
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202280049145.3A Pending CN117677959A (zh) | 2021-06-10 | 2022-06-08 | 使用经训练的机器学习管线识别分类层次结构 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US20220398445A1 (https=) |
| EP (1) | EP4352655A1 (https=) |
| JP (1) | JP2024528393A (https=) |
| CN (1) | CN117677959A (https=) |
| WO (1) | WO2022261233A1 (https=) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US12093864B2 (en) * | 2021-05-18 | 2024-09-17 | Ebay Inc. | Inventory item prediction and listing recommendation |
| US20220415524A1 (en) * | 2021-06-29 | 2022-12-29 | International Business Machines Corporation | Machine learning-based adjustment of epidemiological model projections with flexible prediction horizon |
| WO2024015964A1 (en) * | 2022-07-14 | 2024-01-18 | SucceedSmart, Inc. | Systems and methods for candidate database querying |
| US11841851B1 (en) * | 2022-07-24 | 2023-12-12 | SAS, Inc. | Systems, methods, and graphical user interfaces for taxonomy-based classification of unlabeled structured datasets |
| US12056214B1 (en) * | 2022-09-29 | 2024-08-06 | Amazon Technologies, Inc. | Systems for automatically correcting categories of items |
| CN115859128B (zh) * | 2023-02-23 | 2023-05-09 | 成都瑞安信信息安全技术有限公司 | 一种基于档案数据交互相似度的分析方法和系统 |
| CN117271674A (zh) * | 2023-08-28 | 2023-12-22 | 杭州数梦工场科技有限公司 | 字段类型识别方法、装置、电子设备及存储介质 |
| WO2026044241A1 (en) * | 2024-08-23 | 2026-02-26 | D. E. Shaw Research, Llc | Modeling molecules with transformer machine-learned models |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9483768B2 (en) * | 2014-08-11 | 2016-11-01 | 24/7 Customer, Inc. | Methods and apparatuses for modeling customer interaction experiences |
| US10282368B2 (en) * | 2016-07-29 | 2019-05-07 | Symantec Corporation | Grouped categorization of internet content |
| US9928448B1 (en) * | 2016-09-23 | 2018-03-27 | International Business Machines Corporation | Image classification utilizing semantic relationships in a classification hierarchy |
| US10679330B2 (en) * | 2018-01-15 | 2020-06-09 | Tata Consultancy Services Limited | Systems and methods for automated inferencing of changes in spatio-temporal images |
| US20190354850A1 (en) * | 2018-05-17 | 2019-11-21 | International Business Machines Corporation | Identifying transfer models for machine learning tasks |
| US20190294999A1 (en) * | 2018-06-16 | 2019-09-26 | Moshe Guttmann | Selecting hyper parameters for machine learning algorithms based on past training results |
| US11693910B2 (en) * | 2018-12-13 | 2023-07-04 | Microsoft Technology Licensing, Llc | Personalized search result rankings |
| US10937417B2 (en) * | 2019-05-31 | 2021-03-02 | Clinc, Inc. | Systems and methods for automatically categorizing unstructured data and improving a machine learning-based dialogue system |
| US11494559B2 (en) * | 2019-11-27 | 2022-11-08 | Oracle International Corporation | Hybrid in-domain and out-of-domain document processing for non-vocabulary tokens of electronic documents |
| US11481448B2 (en) * | 2020-03-31 | 2022-10-25 | Microsoft Technology Licensing, Llc | Semantic matching and retrieval of standardized entities |
| US11687812B2 (en) * | 2020-08-18 | 2023-06-27 | Accenture Global Solutions Limited | Autoclassification of products using artificial intelligence |
-
2021
- 2021-06-10 US US17/303,918 patent/US20220398445A1/en active Pending
-
2022
- 2022-06-08 EP EP22740694.9A patent/EP4352655A1/en not_active Withdrawn
- 2022-06-08 JP JP2023575783A patent/JP2024528393A/ja active Pending
- 2022-06-08 WO PCT/US2022/032705 patent/WO2022261233A1/en not_active Ceased
- 2022-06-08 CN CN202280049145.3A patent/CN117677959A/zh active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| EP4352655A1 (en) | 2024-04-17 |
| US20220398445A1 (en) | 2022-12-15 |
| WO2022261233A1 (en) | 2022-12-15 |
| JP2024528393A (ja) | 2024-07-30 |
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