CA3212044A1 - Infrastructure de validation a apprentissage automatique et gestion de fonctions d?entite - Google Patents
Infrastructure de validation a apprentissage automatique et gestion de fonctions d?entite Download PDFInfo
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- CA3212044A1 CA3212044A1 CA3212044A CA3212044A CA3212044A1 CA 3212044 A1 CA3212044 A1 CA 3212044A1 CA 3212044 A CA3212044 A CA 3212044A CA 3212044 A CA3212044 A CA 3212044A CA 3212044 A1 CA3212044 A1 CA 3212044A1
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- 238000010200 validation analysis Methods 0.000 title claims abstract description 85
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- General Physics & Mathematics (AREA)
- Medical Informatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Artificial Intelligence (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Transplanting Machines (AREA)
- General Factory Administration (AREA)
- Mobile Radio Communication Systems (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
La présente invention concerne un système et un procédé pour une détection à apprentissage automatique de valeurs aberrantes dans des demandes de charge utile. Un système de gestion d?entités utilise un apprentissage automatique pour regrouper des données caractérisant des demandes provenant d?entités pour acheminer des charges utiles, et détermine un ou plusieurs groupes de données qui sont des valeurs aberrantes. Le système reçoit une demande d?acheminement d?une charge utile vers une destination et applique un modèle d?apprentissage automatique supervisé à des informations de taille et de type indiquées par la charge utile. Le modèle d?apprentissage automatique supervisé applique une étiquette aux données de charge utile (par exemple, indiquant que la demande d?acheminement de charge utile est une valeur aberrante). Cette détection de valeur aberrante peut diriger un processus de validation pour traiter des valeurs aberrantes détectées. Le système peut recevoir une indication pour réaliser une fonction de validation et transmettre la charge utile à une destination de validation. Le système peut exploiter des données de charge utile et des rétroinformations reçues en provenance d?une entité pour optimiser des techniques d?apprentissage automatique pour l?entité.
Applications Claiming Priority (9)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US202117222981A | 2021-04-05 | 2021-04-05 | |
| US17/222,981 | 2021-04-05 | ||
| US17/222,972 US20220318670A1 (en) | 2021-04-05 | 2021-04-05 | Machine-learned entity function management |
| US17/222,972 | 2021-04-05 | ||
| US17/224,808 US11238376B1 (en) | 2021-04-05 | 2021-04-07 | Machine-learned validation framework |
| US17/224,808 | 2021-04-07 | ||
| US17/224,828 | 2021-04-07 | ||
| US17/224,828 US11410085B1 (en) | 2021-04-05 | 2021-04-07 | Machine-learned entity function management |
| PCT/US2022/023260 WO2022216582A1 (fr) | 2021-04-05 | 2022-04-04 | Infrastructure de validation à apprentissage automatique et gestion de fonctions d'entité |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA3212044A1 true CA3212044A1 (fr) | 2022-10-13 |
Family
ID=83546446
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA3212044A Pending CA3212044A1 (fr) | 2021-04-05 | 2022-04-04 | Infrastructure de validation a apprentissage automatique et gestion de fonctions d?entite |
Country Status (3)
| Country | Link |
|---|---|
| AU (1) | AU2022254638A1 (fr) |
| CA (1) | CA3212044A1 (fr) |
| WO (1) | WO2022216582A1 (fr) |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8682820B2 (en) * | 2011-11-02 | 2014-03-25 | Sap Ag | On demand multi-objective network optimization |
| US9900342B2 (en) * | 2014-07-23 | 2018-02-20 | Cisco Technology, Inc. | Behavioral white labeling |
| US9729571B1 (en) * | 2015-07-31 | 2017-08-08 | Amdocs Software Systems Limited | System, method, and computer program for detecting and measuring changes in network behavior of communication networks utilizing real-time clustering algorithms |
| US20180330278A1 (en) * | 2017-05-09 | 2018-11-15 | TAYGO Inc. | Processes and techniques for more effectively training machine learning models for topically-relevant two-way engagement with content consumers |
| US11954881B2 (en) * | 2018-08-28 | 2024-04-09 | Apple Inc. | Semi-supervised learning using clustering as an additional constraint |
| US11238376B1 (en) * | 2021-04-05 | 2022-02-01 | Tekion Corp | Machine-learned validation framework |
-
2022
- 2022-04-04 WO PCT/US2022/023260 patent/WO2022216582A1/fr active Application Filing
- 2022-04-04 CA CA3212044A patent/CA3212044A1/fr active Pending
- 2022-04-04 AU AU2022254638A patent/AU2022254638A1/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022216582A1 (fr) | 2022-10-13 |
| AU2022254638A1 (en) | 2023-09-21 |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| EEER | Examination request |
Effective date: 20230914 |
|
| EEER | Examination request |
Effective date: 20230914 |