PATENT CLAIM ANALYSIS

Application Number: 15917463
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["705", "044000"]

Abstract:
Systems and methods for applying machine learning to dynamically validate a sales transaction document created by a user in a computing system are provided. Data comprising the sales transaction document is received. A machine learning model is applied to the sales transaction document to verify that the sales transaction document meets at least one compliance standard. The user is alerted if the sales transaction document does not meet the at least one compliance standard. The maching learning model is generated by: receiving first sales transaction data from a database; determining patterns based on the first sales transaction data, wherein the patterns indicate that corrective data was created to compensate for at least one error in original data, the at least one error indicating that the original data did not meet at least one compliance standard; and generating the machine learning model based on the determined patterns.

Claim (Index 2):
The computer-implemented method of  claim 1 , further comprising:\n receiving second sales transaction data from the database; adjusting the machine learning model based on the second sales transaction data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 2.22857
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13301031', '15354883', '09710543', '10030139', '12040213']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1044588655709919
- 35 USC 102 Novelty (BERT): 0.4683108174935692
- Combined Prediction Score: 0.1408440607632497
- Mean Citation Score: 160.93870199999995
- Max Citation Score: 165.76148999999995
- Similarity Product: 124.24089064360138

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