USPTO Patent Grant for Feature Space Management
Summary
The USPTO has granted patent US12585705B2 to LEMON INC. for a method of feature space management in data samples, utilizing global and local representations to capture domain-specific knowledge. The patent was granted on March 24, 2026.
What changed
The United States Patent and Trademark Office (USPTO) has issued patent US12585705B2 to LEMON INC. for a novel method of managing feature spaces in data samples. This patent, granted on March 24, 2026, describes techniques for generating a feature representation by combining global and local representations, aiming to create exclusive feature spaces for different domains to capture specific knowledge and characteristics. The patent application was filed on August 29, 2023, and includes 18 claims.
This patent grant represents a new intellectual property asset for LEMON INC. and potentially impacts companies developing AI and machine learning technologies, particularly those focused on data sample analysis and domain-specific feature extraction. While this is a patent grant and not a regulatory rule imposing direct compliance obligations, companies operating in AI and data analytics should be aware of this patented technology, as it may affect their freedom to operate or require licensing for similar functionalities. No immediate compliance actions are required for entities outside of LEMON INC., but legal and R&D departments should assess potential IP conflicts.
Source document (simplified)
Feature space management
Grant US12585705B2 Kind: B2 Mar 24, 2026
Assignee
LEMON INC.
Inventors
Meng Xin, Silun Wang, Huang Zou, Yu Zhang
Abstract
There are proposed methods, devices, and computer program products for extending a feature space of a data sample. In the method, a global representation is obtained for a feature in a plurality of features of the data sample. A local representation is obtained for the feature based on a classifying criterion for classifying the data sample into one of a plurality of predefined domains. A representation is generated for the feature of the data sample based on the global representation and the local representation. With these implementations, an exclusive feature space may be created for each domain identified by the classifying criterion, which is dedicated to capturing domain-specific knowledge and characteristics.
CPC Classifications
G06F 16/906 G06V 10/7715 G06N 20/00
Filing Date
2023-08-29
Application No.
18458001
Claims
18
Named provisions
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