CA3096405A1 - Traitement de donnees personnelles a l'aide d'algorithmes d'apprentissage machine, et applications associees - Google Patents
Traitement de donnees personnelles a l'aide d'algorithmes d'apprentissage machine, et applications associees Download PDFInfo
- Publication number
- CA3096405A1 CA3096405A1 CA3096405A CA3096405A CA3096405A1 CA 3096405 A1 CA3096405 A1 CA 3096405A1 CA 3096405 A CA3096405 A CA 3096405A CA 3096405 A CA3096405 A CA 3096405A CA 3096405 A1 CA3096405 A1 CA 3096405A1
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Links
- 238000010801 machine learning Methods 0.000 title claims description 30
- 238000012545 processing Methods 0.000 title description 3
- 238000012549 training Methods 0.000 claims abstract description 79
- 238000000034 method Methods 0.000 claims description 102
- 230000008569 process Effects 0.000 claims description 38
- 230000037406 food intake Effects 0.000 claims description 34
- 230000036541 health Effects 0.000 claims description 19
- 238000012544 monitoring process Methods 0.000 claims description 14
- 238000001914 filtration Methods 0.000 claims description 4
- 230000000737 periodic effect Effects 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 28
- 239000008186 active pharmaceutical agent Substances 0.000 description 14
- 238000012795 verification Methods 0.000 description 9
- 238000004140 cleaning Methods 0.000 description 6
- 230000008859 change Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000012552 review Methods 0.000 description 4
- 230000006399 behavior Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 230000003542 behavioural effect Effects 0.000 description 2
- 229940079593 drug Drugs 0.000 description 2
- 239000003814 drug Substances 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 230000002085 persistent effect Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000012517 data analytics Methods 0.000 description 1
- 238000013479 data entry Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000007477 logistic regression Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012706 support-vector machine Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
Classifications
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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
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/335—Filtering based on additional data, e.g. user or group profiles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
- G06N20/20—Ensemble learning
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Medical Treatment And Welfare Office Work (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Pour former des modèles, des données d'apprentissage sont nécessaires. Étant donné que les données personnelles changent au fil du temps, les données d'apprentissage peuvent devenir périmées, ce qui empêche leur utilité dans l'apprentissage du modèle. Des modes de réalisation de l'invention traitent ce problème en développant une base de données avec un journal de fonctionnement spécifiant la manière dont des données de chaque personne sont en train d'évoluer. Lorsque des données sont ingérées, elles peuvent ne pas être normalisées. Pour gérer ce problème, des modes de réalisation nettoient les données pour garantir que les champs de données ingérés sont normalisés. Enfin, les diverses tâches nécessaires pour entraîner le modèle et résoudre la précision des données personnelles peuvent rapidement devenir encombrantes pour un dispositif informatique. Elles peuvent entrer en conflit les unes avec les autres et entrer en concurrence inefficace pour des ressources de calcul, telles que la puissance du processeur et la capacité de mémoire. Pour traiter ces problèmes, un ordonnanceur est employé pour mettre en file d'attente les diverses tâches impliquées.
Applications Claiming Priority (7)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US15/948,604 US11568302B2 (en) | 2018-04-09 | 2018-04-09 | Training machine learning algorithms with temporally variant personal data, and applications thereof |
| US15/948,646 US20190311372A1 (en) | 2018-04-09 | 2018-04-09 | Normalizing Ingested Personal Data, and Applications Thereof |
| US15/948,646 | 2018-04-09 | ||
| US15/948,652 US10990900B2 (en) | 2018-04-09 | 2018-04-09 | Scheduling machine learning tasks, and applications thereof |
| US15/948,652 | 2018-04-09 | ||
| US15/948,604 | 2018-04-09 | ||
| PCT/US2019/026524 WO2019199778A1 (fr) | 2018-04-09 | 2019-04-09 | Traitement de données personnelles à l'aide d'algorithmes d'apprentissage machine, et applications associées |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA3096405A1 true CA3096405A1 (fr) | 2019-10-17 |
Family
ID=68164473
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA3096405A Pending CA3096405A1 (fr) | 2018-04-09 | 2019-04-09 | Traitement de donnees personnelles a l'aide d'algorithmes d'apprentissage machine, et applications associees |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP3776376A4 (fr) |
| CN (1) | CN112189206B (fr) |
| CA (1) | CA3096405A1 (fr) |
| WO (1) | WO2019199778A1 (fr) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111159861B (zh) * | 2019-12-16 | 2022-04-05 | 北京航空航天大学 | 基于数据包络分析的锂电池多源可靠性试验数据评价方法 |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7167842B1 (en) * | 2000-06-27 | 2007-01-23 | Ncr Corp. | Architecture and method for operational privacy in business services |
| CN102831012A (zh) * | 2011-06-16 | 2012-12-19 | 日立(中国)研究开发有限公司 | 多节点分布式系统中的任务调度装置和任务调度方法 |
| US20130006655A1 (en) * | 2011-06-30 | 2013-01-03 | Verizon Patent And Licensing Inc. | Near real-time healthcare fraud detection |
| US8849730B2 (en) * | 2011-12-15 | 2014-09-30 | Microsoft Corporation | Prediction of user response actions to received data |
| US9218470B2 (en) * | 2012-12-31 | 2015-12-22 | General Electric Company | Systems and methods for non-destructive testing user profiles |
| EP3074877A4 (fr) * | 2013-11-27 | 2017-09-06 | NTT Docomo, Inc. | Classification automatique de tâches basée sur l'apprentissage machine |
| US10296843B2 (en) * | 2014-09-24 | 2019-05-21 | C3 Iot, Inc. | Systems and methods for utilizing machine learning to identify non-technical loss |
| US10713594B2 (en) * | 2015-03-20 | 2020-07-14 | Salesforce.Com, Inc. | Systems, methods, and apparatuses for implementing machine learning model training and deployment with a rollback mechanism |
| CN105007282B (zh) * | 2015-08-10 | 2018-08-10 | 济南大学 | 面向网络服务提供商的恶意软件网络行为检测方法及系统 |
| CN105117477B (zh) * | 2015-09-09 | 2018-07-31 | 中国人民解放军国防科学技术大学 | 一种自适应自反馈的虚拟资产异常发现系统及实现方法 |
| WO2018017467A1 (fr) * | 2016-07-18 | 2018-01-25 | NantOmics, Inc. | Systèmes, appareils et procédés d'apprentissage automatique distribué |
| CN106875270A (zh) * | 2017-01-19 | 2017-06-20 | 上海冰鉴信息科技有限公司 | 一种构建及验证信用评分方程的方法和系统设计 |
-
2019
- 2019-04-09 CN CN201980024828.1A patent/CN112189206B/zh active Active
- 2019-04-09 EP EP19786111.5A patent/EP3776376A4/fr not_active Withdrawn
- 2019-04-09 CA CA3096405A patent/CA3096405A1/fr active Pending
- 2019-04-09 WO PCT/US2019/026524 patent/WO2019199778A1/fr unknown
Also Published As
| Publication number | Publication date |
|---|---|
| EP3776376A4 (fr) | 2021-12-01 |
| WO2019199778A1 (fr) | 2019-10-17 |
| CN112189206B (zh) | 2024-09-06 |
| EP3776376A1 (fr) | 2021-02-17 |
| CN112189206A (zh) | 2021-01-05 |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| EEER | Examination request |
Effective date: 20220928 |
|
| EEER | Examination request |
Effective date: 20220928 |
|
| EEER | Examination request |
Effective date: 20220928 |
|
| EEER | Examination request |
Effective date: 20220928 |
|
| EEER | Examination request |
Effective date: 20220928 |
|
| EEER | Examination request |
Effective date: 20220928 |