PATENT CLAIM ANALYSIS

Application Number: 16042971
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-04
Patent Classification: ["717", "168000"]

Abstract:
Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.

Claim (Index 16):
The one or more non-transitory computer-readable media of  claim 15 , the operations further comprising reconciling configuration settings for deployments that belong to the at least one cluster based on the representative node by updating configuration settings for the deployments to match the configuration settings corresponding to the representative node.

Metadata:
- Claim Count in Document: 62.0
- Percentile: 95.0
- Lexical Diversity: 2.35
- Patent Class: 717.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16041269', '15264975', '15899529', '15899625', '13733288']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3594281711459858
- 35 USC 102 Novelty (BERT): 0.516244445865294
- Combined Prediction Score: 0.3751097986179167
- Mean Citation Score: 159.58884600000005
- Max Citation Score: 244.66595
- Similarity Product: 159.3993964950919

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