公开(公告)号：US20250148431A1

公开(公告)日：2025-05-08

申请号：US18938823

申请日：2024-11-06

Applicant: NEC Laboratories America, Inc.

Inventor： Haoyu Wang ,  Christopher A. White ,  Haifeng Chen ,  LuAn Tang ,  Zhengzhang Chen ,  Xujiang Zhao

IPC: G06Q10/30 ,  G06Q10/0637

Abstract: Systems and methods for an agent-based carbon emission reduction system. A carbon product of a supply chain system can be limited below a carbon product threshold by performing a corrective action to monitored entities based on a calculated carbon emission. The carbon emission can be calculated based on carbon-relevant data and a calculation route by utilizing an agent-based simulation model that simulates a learned relationship between a supply chain system and the carbon-relevant data. The calculation route can be determined based on the carbon-relevant data based on a relevance of a carbon product contribution of monitored entities to a goal of the monitored entities. Carbon-relevant data can be extracted from the monitored entities.

公开(公告)号：US20240338393A1

公开(公告)日：2024-10-10

申请号：US18628271

申请日：2024-04-05

Applicant: NEC Laboratories America, Inc.

Inventor： Christopher Malon ,  Iain Melvin ,  Christopher A. White

IPC: G06F16/332 ,  G06F16/338 ,  G06F40/30

CPC classification number: G06F16/3323 ,  G06F16/338 ,  G06F40/30

Abstract: Systems and methods are provided for analyzing and visualizing document corpuses based on user-defined semantic features, including initializing a Natural Language Inference (NLI) classification model pre-trained on a diverse linguistic dataset, analyzing a corpus of textual documents with semantic features described in natural language by a user. For each semantic feature, a classification process is executed using the NLI model to assess implication strength between sentences in the documents and the semantic feature, the classification process including a confidence scoring mechanism to quantify implication strength. Implication scores can be aggregated for each of the documents to form a composite semantic implication profile, and a dimensionality reduction technique, can be applied to the composite semantic implication profiles of each of the documents to generate a two-dimensional semantic space representation. The two-dimensional semantic space representation can be dynamically adjusted based on iterative user feedback regarding the accuracy of semantic implication assessments.