PATENT CLAIM ANALYSIS

Application Number: 16256807
Application Type: Utility
Filing Date: 2019-01
Publication Date: 2019-06
Patent Classification: ["726", "022000"]

Abstract:
Described are techniques to enable computers to efficiently determine if they should run a program based on an immediate (i.e., real-time, etc.) analysis of the program. Such an approach leverages highly trained ensemble machine learning algorithms to create a real-time discernment on a combination of static and dynamic features collected from the program, the computer's current environment, and external factors. Related apparatus, systems, techniques and articles are also described.

Claim (Index 31):
A computer-implemented method comprising:\n receiving a plurality of features derived from at least two sources to enable a determination of whether at least a portion of a program should be allowed to execute or continue to execute; determining, based on the plurality of features by a trained machine learning model, whether to allow at least the portion of the program to execute or continue to execute; allowing at least the portion of the program to execute or continue to execute, when the machine learning model determines that at least the portion of the program is allowed to execute or continue to execute; and preventing at least the portion of the program from executing or continuing to execute, when the machine learning model determines that at least the portion of the program is not allowed to execute or continue to execute; wherein the at least two sources are selected from a group consisting of: operational features that relate to an operational environment of the system, static features that are associated with the program, dynamic features that relate to execution of the program, or external features that are extracted from a source other than the system executing the program.

Metadata:
- Claim Count in Document: 65.0
- Percentile: 99.0
- Lexical Diversity: 1.41379
- Patent Class: 726.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14616509', '15252106', '15615609', '14663701', '15216661']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2828246996785877
- 35 USC 102 Novelty (BERT): 0.5072515170165514
- Combined Prediction Score: 0.3052673814123841
- Mean Citation Score: 199.331836
- Max Citation Score: 297.80548
- Similarity Product: 234.09889704652787

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