PATENT CLAIM ANALYSIS

Application Number: 15990032
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-07
Patent Classification: ["717", "124000"]

Abstract:
Machine learning techniques are used to determine the viability of user data measuring the behavior of a new version of the program when compared with user data that measured the behavior of a previous version of the program. The machine learning techniques utilize statistical techniques in a non-conventional manner to train a system to learn from data obtained from the usage of both a new version of the program and a previous version that accounts for the variability in the user population, time variability of the results of the previous version, and feature coverage between the two test results in order to ensure the suitability of the user data in making estimations or predictions about the performance and reliability of the new version.

Claim (Index 4):
The system of  claim 3 , wherein a proportion of percentage test is used to perform the comparison.

Metadata:
- Claim Count in Document: 46.0
- Percentile: 93.0
- Lexical Diversity: 2.04839
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14198284', '14198271', '14865384', '14877923', '13796923']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3767510482745335
- 35 USC 102 Novelty (BERT): 0.5180137630091859
- Combined Prediction Score: 0.3908773197479987
- Mean Citation Score: 146.21510999999995
- Max Citation Score: 154.44724
- Similarity Product: 82.043523328166

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

Dataset: test