PATENT CLAIM ANALYSIS

Application Number: 16133467
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2020-01
Patent Classification: ["706", "020000"]

Abstract:
According to an exemplary embodiment of the present disclosure, disclosed is a computer program stored in a computer readable storage medium. When the computer program is executed in one or more processors, the computer program performs the following method for anomaly detection of data using a network function, and the method includes: generating an anomaly detection model including a plurality of anomaly detection sub models including a trained network function using a plurality of training data sub sets included in the training data set; calculating input data using at least one of the plurality of generated anomaly detection sub models; and determining whether there is an anomaly in the input data based on output data for input data of at least one of the plurality of generated anomaly detection sub models and the input data.

Claim (Index 9):
The computer program stored in a computer readable storage medium according to  claim 1 , wherein the determining of whether there is an anomaly in the input data includes:\n determining whether there is an anomaly in the input data, based on a reconstruction error calculated based on the comparison of the output data and the input data.

Metadata:
- Claim Count in Document: 35.0
- Percentile: 97.0
- Lexical Diversity: 2.26984
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['13049032', '11940790', '15284246', '13778064', '13198900']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4020308262851895
- 35 USC 102 Novelty (BERT): 0.4898540824237513
- Combined Prediction Score: 0.4108131518990457
- Mean Citation Score: 221.76974
- Max Citation Score: 225.40419
- Similarity Product: 164.05539257281958

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

Dataset: test