PATENT CLAIM ANALYSIS

Application Number: 15964928
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-10
Patent Classification: ["717", "170000"]

Abstract:
A method and apparatus for data driven and cluster specific version/update control. The apparatus includes an automated multi-clusters management apparatus that interfaces with a plurality of remote clusters to provide data driven version/update control on a cluster by cluster basis. Generally, operation includes collection/identification of cluster specific data pertaining to software, hardware, and cluster requirements. The cluster specific data is later compared/analyzed against multi-cluster data pertaining to software releases, hardware characteristics, and known bugs/issues for each. The results of the comparison/analysis can then be ranked according to various metrics to different possible solutions and to differentiate the less desirable results from the more desirable results. Thus, the automated multi-cluster management apparatus provides for selection of versions/updates that is dependent on the cluster specific data. Additionally, the present disclosure provides for scheduling and distribution planning for selected versions/updates.

Claim (Index 17):
A system, comprising:\n a memory for storing a sequence of instructions; and a processor that executes the sequence of instructions to perform a set of acts, the set of acts comprising: ranking a set of candidate releases based on a metric, wherein a ranking of a candidate release is lowered based on a machine learning process and a specific combination of hardware and software for the candidate release; selecting an update to be installed on a cluster based on at least the ranking of the set of candidate release; and scheduling installation of the update on a node of the cluster over a first time period using a rule, wherein the rule is modified by a machine learning process based on a difference between an expected time period for completion and an actual time period for completion.

Metadata:
- Claim Count in Document: 33.0
- Percentile: 91.0
- Lexical Diversity: 1.91139
- Patent Class: 717.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13636061', '15815299', '15259630', '14038661', '15959237']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3583977624009463
- 35 USC 102 Novelty (BERT): 0.4973072453107093
- Combined Prediction Score: 0.3722887106919226
- Mean Citation Score: 142.40150400000005
- Max Citation Score: 145.02924
- Similarity Product: 90.9317478174233

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