PATENT CLAIM ANALYSIS

Application Number: 16218195
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-10
Patent Classification: ["718", "100000"]

Abstract:
Disclosed are a method and apparatus for automatically scheduling jobs in computer numerical control machines using machine learning. The method includes collecting a schedule job list from a database, generating a plurality of schedules for a schedule job to be processed with respect to the schedule job list, calculating an evaluation index for the plurality of generated schedules, determining whether the calculated evaluation index for the plurality of schedules has reached a target evaluation index, selecting a schedule corresponding to two evaluation indices when the calculated evaluation index does not reach the target evaluation index and generating two new schedules using a genetic algorithm, and setting a selection probability so that a schedule having the highest evaluation index is selected and returning the selection probability to a user when the calculated evaluation index reaches the target evaluation index.

Claim (Index 11):
The apparatus of  claim 10 , further comprising a display unit configured to incorporate the schedule returned to the user into job assignment information for each machine and to display the job assignment information for each machine.

Metadata:
- Claim Count in Document: 20.0
- Percentile: 98.0
- Lexical Diversity: 2.01389
- Patent Class: 718.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['12334561', '13353109', '11845968', '09656393', '12686537']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4349395595613456
- 35 USC 102 Novelty (BERT): 0.521025983487947
- Combined Prediction Score: 0.4435482019540058
- Mean Citation Score: 191.99532600000003
- Max Citation Score: 198.15977
- Similarity Product: 122.35429307688833

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

Dataset: test