PATENT CLAIM ANALYSIS

Application Number: 16019021
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-11
Patent Classification: ["704", "009000"]

Abstract:
A method performed by a device may include identifying a plurality of samples of textual content; performing tokenization of the plurality of samples to generate a respective plurality of tokenized samples; performing embedding of the plurality of tokenized samples to generate a sample matrix; determining groupings of attributes of the sample matrix using a convolutional neural network; determining context relationships between the groupings of attributes using a bidirectional long short term memory (LSTM) technique; selecting predicted labels for the plurality of samples using a model, wherein the model selects, for a particular sample of the plurality of samples, a predicted label of the predicted labels from a plurality of labels based on respective scores of the particular sample with regard to the plurality of labels and based on a nonparametric paired comparison of the respective scores; and providing information identifying the predicted labels.

Claim (Index 16):
The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to:\n determine the respective scores based on a Monte Carlo simulation using a dropout technique.

Metadata:
- Claim Count in Document: 56.0
- Percentile: 94.0
- Lexical Diversity: 2.31343
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13971092', '15994278', '15886873', '15670886', '14720113']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2744380012041988
- 35 USC 102 Novelty (BERT): 0.4787358476937743
- Combined Prediction Score: 0.2948677858531563
- Mean Citation Score: 168.27526399999996
- Max Citation Score: 186.96086
- Similarity Product: 138.4139334269905

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