PATENT CLAIM ANALYSIS

Application Number: 15917952
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["370", "242000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for telecommunications network troubleshooting. In one aspect, a method includes obtaining multiple current observations characterizing current operation of a telecommunications network, the multiple observations including performance monitoring data for the network and quality of service data for the network. One or more prior network states for the network are obtained. A current state of the network is determined, by a machine learning model, based on the current observations and the one or more prior network states. One or more actions are performed based on the current state of the network, including, when the current state of the network is an abnormal state, taking an action that is mapped to the abnormal state.

Claim (Index 5):
The method of  claim 1 , wherein determining, by the machine learning model, the current state of the network comprises:\n obtaining, by the one or more data processors, prior observations characterizing prior operation of the network; and jointly processing the prior observations and the current observations in accordance with the current values of the set of machine learning model parameters to generate an output indicating the current state of the network.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 2.27419
- Patent Class: 370.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15091840', '15349894', '14821549', '14097862', '15016173']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4995717145919093
- 35 USC 102 Novelty (BERT): 0.489750266836799
- Combined Prediction Score: 0.4985895698163983
- Mean Citation Score: 176.2632
- Max Citation Score: 185.27437
- Similarity Product: 131.23904528584006

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

Dataset: test