PATENT CLAIM ANALYSIS

Application Number: 16286103
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-08
Patent Classification: ["706", "011000"]

Abstract:
Systems and methods for implementing and using a data modeling and machine learning lifecycle management platform that facilitates collaboration among data engineering, development and operations teams and provides capabilities to experiment using different models in a production environment to accelerate the innovation cycle. Stored computer instructions and processors instantiate various modules of the platform. The modules include a user interface, a collector module for accessing various data sources, a workflow module for processing data received from the data sources, a training module for executing stored computer instructions to train one or more data analytics models using the processed data, a predictor module for producing predictive datasets based on the data analytics models, and a challenger module for executing multi-sample hypothesis testing of the data analytics models.

Claim (Index 33):
The method of  claim 15  wherein the processing nodes comprise one or more collector nodes, and wherein the method further comprises:\n accessing the one or more data sources, each data source providing data for use in training and executing the data analytics plan, and presenting each data source as one of the one or more collector nodes in the user interface.

Metadata:
- Claim Count in Document: 92.0
- Percentile: 99.0
- Lexical Diversity: 1.77632
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15896618', '14838546', '16176833', '13421831', '15375186']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3218285744180365
- 35 USC 102 Novelty (BERT): 0.5916591208628993
- Combined Prediction Score: 0.3488116290625227
- Mean Citation Score: 231.362044
- Max Citation Score: 532.1151
- Similarity Product: 408.3651548774063

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

Dataset: test