PATENT CLAIM ANALYSIS

Application Number: 16362237
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-07
Patent Classification: ["345", "555000"]

Abstract:
Data may be handled based on compressibility (i.e., whether the data may be further compressed or is not further compressible). A supervised learning model may be trained using a set of known further compressible data and a set of known non-compressible data. Using these data sets, the model may generate weighting factors and bias for the particular data sets. The trained model may then be used to evaluate a set of unclassified data.

Claim (Index 9):
A computer system for handling data based on compressibility, the system comprising at least one computer processor circuit configured to perform a method comprising:\n training, using sample data, a supervised learning model, wherein the training comprises determining weighting factors and bias for the supervised learning model, and wherein the sample data comprises a set of known further compressible data and a set of known non-compressible data; and evaluating, using the trained supervised learning model, a set of unclassified data.

Metadata:
- Claim Count in Document: 45.0
- Percentile: 99.0
- Lexical Diversity: 1.6875
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15465850', '14792585', '11203510', '12748921', '14963061']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6095111391115492
- 35 USC 102 Novelty (BERT): 0.4876717093039693
- Combined Prediction Score: 0.5973271961307912
- Mean Citation Score: 147.61709420000005
- Max Citation Score: 232.30807
- Similarity Product: 181.5099126704472

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