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Extract from the Register of European Patents

EP About this file: EP3963469

EP3963469 - LEARNED RESOURCE CONSUMPTION MODEL FOR OPTIMIZING BIG DATA QUERIES [Right-click to bookmark this link]
StatusThe patent has been granted
Status updated on  27.04.2024
Database last updated on 02.09.2024
FormerGrant of patent is intended
Status updated on  19.11.2023
FormerRequest for examination was made
Status updated on  04.02.2022
FormerThe international publication has been made
Status updated on  06.11.2020
Formerunknown
Status updated on  02.05.2020
Most recent event   Tooltip07.06.2024Correction of patent specificationpublished on 10.07.2024  [2024/28]
Applicant(s)For all designated states
Microsoft Technology Licensing, LLC
One Microsoft Way
Redmond, WA 98052-6399 / US
[2022/10]
Inventor(s)01 / SIDDIQUI, Tarique Ashraf
Microsoft Technology Licensing, LLC
One Microsoft Way
Redmond, Washington 98052-6399 / US
02 / JINDAL, Alekh
Microsoft Technology Licensing, LLC
One Microsoft Way
Redmond, Washington 98052-6399 / US
03 / QIAO, Shi
Microsoft Technology Licensing, LLC
One Microsoft Way
Redmond, Washington 98052-6399 / US
04 / PATEL, Hiren S.
Microsoft Technology Licensing, LLC
One Microsoft Way
Redmond, Washington 98052-6399 / US
 [2022/10]
Representative(s)Grünecker Patent- und Rechtsanwälte PartG mbB
Leopoldstraße 4
80802 München / DE
[2022/10]
Application number, filing date20720888.531.03.2020
[2022/10]
WO2020US26018
Priority number, dateUS201962840897P30.04.2019         Original published format: US 201962840897 P
US20191651196615.07.2019         Original published format: US201916511966
[2022/10]
Filing languageEN
Procedural languageEN
PublicationType: A1 Application with search report
No.:WO2020222961
Date:05.11.2020
Language:EN
[2020/45]
Type: A1 Application with search report 
No.:EP3963469
Date:09.03.2022
Language:EN
The application published by WIPO in one of the EPO official languages on 05.11.2020 takes the place of the publication of the European patent application.
[2022/10]
Type: B1 Patent specification 
No.:EP3963469
Date:29.05.2024
Language:EN
[2024/22]
Type: B8 Corrected title page of specification 
No.:EP3963469
Date:10.07.2024
[2024/28]
Search report(s)International search report - published on:EP05.11.2020
ClassificationIPC:G06F16/2453
[2022/10]
CPC:
G06F16/24542 (EP,US); G06F16/211 (US); G06F16/2246 (US);
G06N20/10 (EP); G06N20/20 (EP,US); G06N3/08 (EP);
G06N5/01 (EP); G06F16/24537 (EP) (-)
Designated contracting statesAL,   AT,   BE,   BG,   CH,   CY,   CZ,   DE,   DK,   EE,   ES,   FI,   FR,   GB,   GR,   HR,   HU,   IE,   IS,   IT,   LI,   LT,   LU,   LV,   MC,   MK,   MT,   NL,   NO,   PL,   PT,   RO,   RS,   SE,   SI,   SK,   SM,   TR [2022/10]
Extension statesBANot yet paid
MENot yet paid
Validation statesKHNot yet paid
MANot yet paid
MDNot yet paid
TNNot yet paid
TitleGerman:ERLERNTES RESSOURCENVERBRAUCHSMODELL ZUR OPTIMIERUNG VON BIG-DATA-ABFRAGEN[2024/24]
English:LEARNED RESOURCE CONSUMPTION MODEL FOR OPTIMIZING BIG DATA QUERIES[2022/10]
French:MODÈLE DE CONSOMMATION DE RESSOURCES APPRIS POUR OPTIMISER DES REQUÊTES DE MÉGADONNÉES[2024/22]
Former [2022/10]LERNENDES RESSOURCENVERBRAUCHSMODELL ZUR OPTIMIERUNG VON GROSSDATENABFRAGEN
Former [2022/10]MODÈLE DE CONSOMMATION DE RESSOURCES APPRISES POUR OPTIMISER DES INTERROGATIONS DE MÉGADONNÉES
Entry into regional phase08.10.2021National basic fee paid 
08.10.2021Designation fee(s) paid 
08.10.2021Examination fee paid 
Examination procedure08.10.2021Examination requested  [2022/10]
08.10.2021Date on which the examining division has become responsible
20.05.2022Amendment by applicant (claims and/or description)
20.11.2023Communication of intention to grant the patent
19.03.2024Fee for grant paid
19.03.2024Fee for publishing/printing paid
19.03.2024Receipt of the translation of the claim(s)
Fees paidRenewal fee
18.02.2022Renewal fee patent year 03
14.02.2023Renewal fee patent year 04
20.03.2024Renewal fee patent year 05
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Cited inInternational search[YA]US2011153593  (ZHOU JINGREN [US], et al);
 [YA]US2017126795  (KUMAR SUBODH [US], et al);
 [A]US2018060389  (HWANG SANGYONG [DE])
The EPO accepts no responsibility for the accuracy of data originating from other authorities; in particular, it does not guarantee that it is complete, up to date or fit for specific purposes.