PATENT CLAIM ANALYSIS

Application Number: 15890009
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["701", "023000"]

Abstract:
An approach is provided for machine learning of physical dividers. The approach, for instance, involves retrieving map data, sensor data, or a combination thereof for a segment of a road. The approach also involves retrieving ground truth data for the segment of the road. The ground truth data, for instance, indicates a true presence or a true absence of the physical divider on the segment of the road. The approach further involves processing the map data, the sensor, or a combination thereof and the ground truth data to train a machine learning model to predict the physical divider using the map data, the sensor data, or a combination thereof as an input. The approach further involves using the trained machine learning model to a generate a physical divider overlay of a map representation of a road network.

Claim (Index 2):
The method of  claim 1 , wherein the physical divider is a fixed roadside or a median structure that separates different traffic flow directions or types.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 88.0
- Lexical Diversity: 3.0
- Patent Class: 701.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15597999', '14578956', '15842444', '16313058', '15464398']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4447822635009002
- 35 USC 102 Novelty (BERT): 0.4947955663262751
- Combined Prediction Score: 0.4497835937834377
- Mean Citation Score: 174.051352
- Max Citation Score: 207.404
- Similarity Product: 132.350728785038

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test