PATENT CLAIM ANALYSIS

Application Number: 15876624
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-10
Patent Classification: ["706", "012000"]

Abstract:
A computing system transforms values in a dataset using of high-cardinality transformation flow definitions in parallel. A transformation flow definition includes flow variables and a transformation method to apply to the flow variables. Per-level values are computed for each variable of each observation vector read from the dataset based on the transformation method. (a) an observation vector is read from the dataset to define a first variable value for each variable. (b) a variable of the flow variables is selected as the current variable. (c) a current value is defined equal to the first variable value for the current variable. (d) a per-level value associated with the current value is selected. (e) the per-level value is output to a transformed input dataset. (f) (b) to (e) are repeated with each remaining variable of as the current variable. (n) (h) to (m) are repeated with each remaining observation vector.

Claim (Index 20):
A method of transforming variable values in an input dataset using a plurality of high-cardinality transformation flow definitions applied in parallel, the method comprising:\n receiving a transformation flow definition, wherein the transformation flow definition includes one or more flow variables and a transformation method to apply to the one or more flow variables; (a) reading, by a computing device, an observation vector from an input dataset to define a first variable value for each variable of the one or more flow variables, (b) selecting, by the computing device, a variable of the one or more flow variables as a current variable; (c) defining, by the computing device, a current value equal to the defined first variable value for the current variable; (d) determining, by the computing device, if the defined current value is a new level or an existing level for the current variable; (e) when the defined current value is the new level, initializing, by the computing device, a statistic value in association with the new level based on the defined current value and the transformation method to define per-level statistics; (f) when the defined current value is the existing level, updating, by the computing device, the statistic value from the defined per-level statistics in association with the existing level based on the defined current value and the transformation method; (g) repeating, by the computing device, (c) to (f) with each remaining variable of the one or more flow variables as a current variable; (h) repeating, by the computing device, (a) to (g) with each remaining observation vector from the input dataset; (i) repeating, by the computing device, the read of the observation vector from the input dataset to define the first variable value for each variable of the one or more flow variables, (j) selecting, by the computing device, a second variable of the one or more flow variables as the current variable; (k) defining, by the computing device, the current value equal to the defined first variable value for the current variable; (l) selecting, by the computing device, the statistic value associated with the defined current value; (m) outputting, by the computing device, the selected statistic value to a transformed input dataset; (n) repeating, by the computing device, (k) to (m) with each remaining variable of the one or more flow variables as the current variable; and (o) repeating, by the computing device, (i) to (n) with each remaining observation vector from the input dataset

Metadata:
- Claim Count in Document: 80.0
- Percentile: 86.0
- Lexical Diversity: 2.8125
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14558136', '14928177', '14314517', '15822462', '14924810']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3226925214664631
- 35 USC 102 Novelty (BERT): 0.4960746085716759
- Combined Prediction Score: 0.3400307301769844
- Mean Citation Score: 206.529888
- Max Citation Score: 214.63927
- Similarity Product: 148.449449930141

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test