PATENT CLAIM ANALYSIS

Application Number: 15892407
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["702", "066000"]

Abstract:
The present disclosure relates to systems and methods for detecting and identifying anomalies within a discrete wavelet database. In one implementation, the system may include one or more memories storing instructions and one or more processors configured to execute the instructions. The instructions may include instructions to receive a new wavelet, convert the net transaction to a wavelet, convert the wavelet to a tensor using an exponential smoothing average, calculate a difference field between the tensor and a field having one or more previous transactions represented as tensors, perform a weighted summation of the difference field to produce a difference vector, apply one or more models to the difference vector to determine a likelihood of the new wavelet representing an anomaly, and add the new wavelet to the field when the likelihood is below a threshold.

Claim (Index 33):
The system of  claim 32 , wherein the one or more atlases map the one or more previous wavelets represented as tensors onto a manifold.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 88.0
- Lexical Diversity: 2.02778
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['10310667', '13616484', '13220115', '12445044', '10414758']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1743732787715827
- 35 USC 102 Novelty (BERT): 0.5041565144693005
- Combined Prediction Score: 0.2073516023413545
- Mean Citation Score: 157.62659000000005
- Max Citation Score: 164.35332
- Similarity Product: 95.22543243397948

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

Dataset: test