PATENT CLAIM ANALYSIS

Application Number: 16133631
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-11
Patent Classification: ["345", "419000"]

Abstract:
Data visualization processes can utilize machine learning algorithms applied to visualization data structures to determine visualization parameters that most effectively provide insight into the data, and to suggest meaningful correlations for further investigation by users. In numerous embodiments, data visualization processes can automatically generate parameters that can be used to display the data in ways that will provide enhanced value. For example, dimensions can be chosen to be associated with specific visualization parameters that are easily digestible based on their importance, e.g. with higher value dimensions placed on more easily understood visualization aspects (color, coordinate, size, etc.). In a variety of embodiments, data visualization processes can automatically describe the graph using natural language by identifying regions of interest in the visualization, and generating text using natural language generation processes. As such, data visualization processes can allow for rapid, effective use of voluminous, high dimensional data sets.

Claim (Index 16):
The data visualization method of  claim 15 , further comprising applying histogram-based splitting in the random forest.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 97.0
- Lexical Diversity: 1.74737
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15276742', '15465528', '11328562', '14866272', '15970567']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6216461891764283
- 35 USC 102 Novelty (BERT): 0.5032893549711079
- Combined Prediction Score: 0.6098105057558963
- Mean Citation Score: 195.50728
- Max Citation Score: 232.37299
- Similarity Product: 146.6776437903321

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