Ebay Inc Patent Portfolio Statistics

Ebay Inc.

Profile Summary

This article summarizes the perfomance of the assignee in the recent years. The overall statistics for this portfolio help to analyze the areas where the assignee is performing well. The filing trend, perfomance across the tech centers and the perfomance of the recent applications has been mentioned below. All the stats are calculated based on the perfomance in USPTO.

How does the overall patent portfolio of Ebay Inc. look like?

Assignee Art Units
Total Applications: 5,872 1,159,219
Granted Patents: 3,657 557,518
Grant Index 70.95% 69.78%
Abandoned/Rejected Applications: 1,497 (29.05%) 241,444 (30.22%)
In-Process Applications: 697 360,257
Average Grant Time: 3.42 Years 3.3 Years
Average Office Actions: 2.45 2.07

Which Technology Area Ebay Inc. is filing most patents in? (Last 10 years)

Art Unit Definition Total Applications
3625 Electronic Commerce 614
3684 Business Methods – Incentive Programs, Coupons; Electronic Shopping; Business Cryptography, Voting; Health Care; Point of Sale, Inventory, Accounting; Business Processing, Electronic Negotiation 324
Opap Parked GAU 202
3691 Business Methods – Finance/Banking/ Insurance 181
3687 Business Methods 136

How many patents are Ebay Inc. filing every year?

Year Total Applications Predicted
2022 0* 553
2021 217* 590
2020 251 526
2019 380 380
2018 376
2017 352
2016 347
2015 407
2014 811
2013 529

*The drop in the number of applications filed in last two years compared to previous years is because applications can take up to 18 months to get published

Recently filed patent applications of Ebay Inc. in USPTO?

Publication number: US20220100846A1
Application number: 17/549,027

Technologies are shown for function level permissions control for smart contract execution to implement permissions policy on a blockchain. Permissions control rules control function calls at a system level utilizing function boundary detection instrumentation in a kernel that executes smart contracts. The detection instrumentation generates a call stack that represents a chain of function calls in the kernel for a smart contract. The permissions control rules are applied to the call stack to implement permissions control policy. Permissions control rules can use dynamic state data in the function call chain. If the dynamic state data observed in function call chains does not meet the requirements defined in the permissions control rules, then the function call can be blocked from executing or completing execution. The permissions control rules can be generated for a variety of different entities, such as a domain, user or resource.

Publication date: 2022-03-31
Applicant: Ebay Inc.
Inventors: Chan Michael

Publication number: US20220092134A1
Application number: 17/544,804

Example embodiments of the present disclosure include a system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for provisioning follow up messages to individuals after an in-store retail shopping experience. Consistent with some embodiments, the method may include identifying an item of interest to an individual while in a retail store. The method may further include detecting the individual leaving the retails store, and in response to the individual leaving the retail store, transmitting a message to a mobile device of the individual to remind the individual of the item of interest.

Publication date: 2022-03-24
Applicant: Ebay Inc.
Inventors: Lars Wensel

Publication number: US20220092367A1
Application number: 17/539,558

Various embodiments described herein utilize multiple levels of generative adversarial networks (GANs) to facilitate generation of digital images based on user-provided images. Some embodiments comprise a first generative adversarial network (GAN) and a second GAN coupled to the first GAN, where the first GAN includes an image generator and at least two discriminators, and the second GAN includes an image generator and at least one discriminator. According to some embodiments, the (first) image generator of the first GAN is trained by processing a user-provided image using the first GAN. For some embodiments, the user-provided image and the first generated image, generated by processing the user-provided image using the first GAN, are combined to produce a combined image. For some embodiments, the (second) image generator of the second GAN is trained by processing the combined image using the second GAN.

Publication date: 2022-03-24
Applicant: Ebay Inc.
Inventors: Omid Poursaeed

How are Ebay Inc.’s applications performing in USPTO?

Application Number Title Status Art Unit Examiner
17/549,027 Highly Scalable Permissioned Block Chains Docketed New Case – Ready for Examination OPAP Central, Docket
17/544,804 Follow-Up Messages After In-Store Shopping Docketed New Case – Ready for Examination OPAP Central, Docket
17/539,558 Generating A Digital Image Using A Generative Adversarial Network Docketed New Case – Ready for Examination OPAP Central, Docket
17/538,491 Data Mesh Based Environmental Augmentation Docketed New Case – Ready for Examination OPAP Central, Docket
17/536,705 Managing Database Offsets With Time Series Docketed New Case – Ready for Examination OPAP Central, Docket