PATENT CLAIM ANALYSIS

Application Number: 15939893
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["717", "128000"]

Abstract:
A multivariate path-based anomaly detection and prediction service (“anomaly detector”) can generate a prediction event for consumption by the APM manager that indicates a likelihood of an anomaly occurring based on path analysis of multivariate values after topology-based feature selection. To predict that a set of metrics will travel to a cluster that represents anomalous application behavior, the anomaly detector analyzes a set of multivariate date slices that are not within a cluster to determine whether dimensionally reduced representations of the set of multivariate data slices fit a path as described by a function.

Claim (Index 1):
A method comprising:\n based on a determination that a first dimensionally reduced representation of a first time-series multivariate dataset of a first set of metrics of a distributed application is not in one of a plurality of clusters that each corresponds with a behavior of the distributed application as represented by the first set of metrics, selecting a first set of dimensionally reduced representations of time-series multivariate datasets that preceded the first time-series multivariate dataset; determining whether the selected first set of dimensionally reduced representations and the first dimensionally reduced representation occur along a first path described by a first time-dependent multivariate function, wherein the first path overlaps with at least a first cluster of the plurality of clusters; and based on a determination that the selected first set of dimensionally reduced representations and the first dimensionally reduced representation occur along the first path with at least a confidence value that satisfies a confidence threshold, generating an event that predicts the first set of metrics of the distributed application will exhibit the behavior corresponding with the first cluster.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 90.0
- Lexical Diversity: 1.48529
- Patent Class: 717.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15894647', '11557584', '14596151', '14586381', '15827663']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3122737775527617
- 35 USC 102 Novelty (BERT): 0.5091547150478835
- Combined Prediction Score: 0.3319618713022739
- Mean Citation Score: 142.90302880000004
- Max Citation Score: 224.49077000000003
- Similarity Product: 165.06241753495038

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