PATENT CLAIM ANALYSIS

Application Number: 15880339
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["706", "020000"]

Abstract:
During training mode, first input data is provided to a first neural network to generate first output data indicating that the first input data is classified in a first cluster. The first input data includes at least one of a continuous feature or a categorical feature. Second input data is generated and provided to at least one second neural network to generate second output data. The at least one second neural network corresponds to a variational autoencoder. An aggregate loss corresponding to the second output data is determined, including at least one of evaluating a first loss function for the continuous feature or evaluating a second loss function for the categorical feature. Based on the aggregate loss, at least one parameter of at least one neural network is adjusted. During use mode, the neural networks are used to determine cluster identifications and anomaly likelihoods for received data samples.

Claim (Index 18):
A computer-readable storage device storing instructions that, when executed, cause a processor to perform operations comprising:\n receiving a data sample that includes at least one of a continuous feature or a categorical feature, wherein the data sample comprises a measurement from a sensor coupled to a device; providing the data sample to a first neural network to generate first output data indicating a cluster identifier (ID) for the data sample; providing input data based on the data sample to at least one second neural network corresponding to a variational auto encoder (VAE) associated with a latent space; providing second input data to a third neural network to determine first mean values and first variance values that represent a mapping for the cluster ID to a region in the latent space; determining an anomaly likelihood for the data sample based on a reconstruction loss associated with the VAE, the first mean values, the first variance values, and second mean values generated at the VAE, the anomaly likelihood indicating a likelihood of an anomaly associated with the device; outputting the cluster ID and the anomaly likelihood; and automatically performing at least one operation based on the cluster ID, the anomaly likelihood, or both.

Metadata:
- Claim Count in Document: 51.0
- Percentile: 86.0
- Lexical Diversity: 2.56452
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15793890', '15489564', '15794980', '15832050', '15600696']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3680851550326703
- 35 USC 102 Novelty (BERT): 0.4643437888378489
- Combined Prediction Score: 0.3777110184131882
- Mean Citation Score: 156.754692
- Max Citation Score: 161.75179
- Similarity Product: 122.89601437224267

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