PATENT CLAIM ANALYSIS

Application Number: 16322095
Application Type: Utility
Filing Date: 2019-01
Publication Date: 2019-06
Patent Classification: ["340", "933000"]

Abstract:
A vehicle type identification method and device based on mobile phone data for solving the problem of providing a convenient and low-cost vehicle type identification method. The method includes: obtaining trajectory data recorded by a mobile phone of a user within a period of time; judging mobile phone users who are on the same vehicle according to the data, and obtaining a vehicle trajectory and the number of passengers corresponding to the vehicle trajectory; obtaining a vehicle origin and destination according to the vehicle trajectory, and obtaining an origin-destination type of the vehicle trajectory in combination with geographic data; obtaining vehicle driving data according to the vehicle trajectory; and obtaining service area data of vehicle staying according to the vehicle trajectory. The cost of obtaining data by using mobile phone big data and by using mobile phone signaling data collected and provided by an operator is low.

Claim (Index 17):
A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to  claim 5  when executing the program.

Metadata:
- Claim Count in Document: 44.0
- Percentile: 99.0
- Lexical Diversity: 2.37879
- Patent Class: 340.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['16321064', '13291730', '13291725', '13291722', '15259954']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6172101376187381
- 35 USC 102 Novelty (BERT): 0.5138706170926245
- Combined Prediction Score: 0.6068761855661268
- Mean Citation Score: 174.28859599999996
- Max Citation Score: 197.33347
- Similarity Product: 119.96239673404637

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

Dataset: test