WO2023067401 - SYSTEMS AND METHODS OF REQUEST GROUPING
National phase entry:
Publication Number
WO/2023/067401
Publication Date
27.04.2023
International Application No.
PCT/IB2022/058009
International Filing Date
26.08.2022
Title **
[English]
SYSTEMS AND METHODS OF REQUEST GROUPING
[French]
SYSTÈMES ET PROCÉDÉS DE REGROUPEMENT DE REQUÊTES
Applicants **
PERION NETWORK LTD.
26 Ha'Rokmim St.
5885849 Holon, IL
Inventors
SHPAK, Adi
Prof Efraim Katsir 25
Rehovot, IL
BERNSTEIN, Anat
Arvei Nachal 11
Givaataim, IL
ORR, Madi
Shderot Nordau 21
Tel Aviv, IL
MEIROVICH, Assaf
Lea Goldberg 6
Herzlia, IL
Priority Data
63/256,706
18.10.2021
US
17/871,510
22.07.2022
US
Application details
| Total Number of Claims/PCT | * |
| Number of Independent Claims | * |
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| Number of Multi-Dependent Claims | * |
| Number of Drawings | * |
| Pages for Publication | * |
| Number of Pages with Drawings | * |
| Pages of Specification | * |
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International Searching Authority |
USPTO
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| Applicant's Legal Status |
Legal Entity
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| Entry into National Phase under |
Chapter I
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| Translation |
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Recalculate
* The data is based on automatic recognition. Please verify and amend if necessary.
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing | 1306 | |
| EPO | Filing, Examination | 7951 | |
| Japan | Filing | 588 | |
| South Korea | Filing | 606 | |
| USA | Filing, Examination | 2280 |
Total: 12731 USD
The term for entry into the National Phase has expired. This quotation is for informational purposes only
Abstract[English]
Apparatuses, systems, and methods of training and utilizing a machine learning model to categorize data requests based on contextual signals. Using a trained machine learning model, a computer system is enabled to provide relevant content to users in the absence of third-party cookies.[French]
La présente invention concerne des appareils, des systèmes et des procédés d'entraînement et d'utilisation d'un modèle d'apprentissage machine pour catégoriser des requêtes de données sur la base de signaux contextuels. À l'aide d'un modèle d'apprentissage machine entraîné, un système informatique est activé pour fournir un contenu pertinent à des utilisateurs en l'absence de témoins de tierce partie.