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 1):
A data visualization system comprising:\n at least one processor; at least one graphics processing module; and a memory comprising a data visualization application, where the data visualization application directs the at least one processor to:\n obtain data comprising a set of records, where each record has at least three data dimensions; \n store the obtained data in a table structure, where each record is represented by a row in the table structure, each dimension is represented by a column in the table structure, and each cell is populated with a value corresponding to the obtained data; \n generate at least one mapping from the at least three data dimensions to a set of visualization dimensions, where the mapping comprises a set of visualization parameters assigned to each column in the table structure, where each visualization parameter in the set of visualization parameters describes how an arbitrary value in the column should be visualized; \n generate a data structure, where the data structure comprises:\n a first list comprising the locations of points in a set of unrendered points, where each unrendered point is located in 3D space and represents values in at least one record; and \n a second list comprising visualization information describing how to render a set of 3D objects, where each 3D object is centered around a respective unrendered point in the set of unrendered points, based on the visualization parameters; and \n render the 3D objects in a virtual 3D environment using the graphics processing module and the data structure, where the graphics processing module renders the 3D point objects in parallel.

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): 0.6264052820975277
- 35 USC 102 Novelty (BERT): 0.4816178074006044
- Combined Prediction Score: 0.6119265346278353
- Mean Citation Score: 195.50728
- Max Citation Score: 232.37299
- Similarity Product: 193.1487625423396

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