Invention Application
- Patent Title: SEQUENTIAL EVENT MODELING FROM MULTIVARIATE CATEGORICAL SENSOR DATA
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Application No.: US18829972Application Date: 2024-09-10
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Publication No.: US20250133099A1Publication Date: 2025-04-24
- Inventor: Peng Yuan , LuAn Tang , Haifeng Chen
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Laboratories America, Inc.
- Current Assignee: NEC Laboratories America, Inc.
- Current Assignee Address: US NJ Princeton
- Main IPC: H04L9/40
- IPC: H04L9/40 ; G06F16/25 ; G06F16/28

Abstract:
Systems and methods include converting historical data into categorical time series data and de-noising the categorical time series data by removing noisy transitions sets according to a coefficient of variation. A likelihood of a category transition is determined based on historical events using a Hawkes process to generate a relationship graph. Relationships between pairs of nodes are determined using the relationship graph, where the relationships indicate a degree of correlation between the nodes based on de-noised categorical time-series data. An anomaly threshold is determined based on anomaly scores for a validation dataset using the relationship graph, wherein a likelihood output of the Hawkes process that exceeds the anomaly threshold indicates an anomaly.
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