PATENT CLAIM ANALYSIS

Application Number: 16055114
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["455", "405000"]

Abstract:
A computer implemented method of predicting a rating score of a cellular service for a plurality of cellular subscribers, comprising obtaining one or more machine learning models trained with a plurality of feature vectors created for a subset of a plurality of cellular subscribers of a cellular operator participating in a survey to rate a cellular service provided by the cellular operator through a cellular network where each of the feature vectors is created by extracting a plurality of features of a respective cellular subscriber of the subset, each feature vector is associated with a rating score assigned by the respective cellular subscriber, predicting an estimated rating score of the cellular service for other cellular subscribers by applying the machine learning model(s) to the feature vector of extracted features of each of the other cellular subscribers and outputting the estimated rating score for each of the other cellular subscribers.

Claim (Index 10):
The computer implemented method of  claim 1 , further comprising predicting said estimated rating score for said at least some cellular subscribers for a segment of said cellular service, said segment is a member of a group consisting of: a section of said cellular network, a certain geographical region, a certain geographical location, a certain segment of said at least some cellular subscribers, a certain type of said cellular service, and a certain cellular device type used by said at least some cellular subscribers.

Metadata:
- Claim Count in Document: 22.0
- Percentile: 96.0
- Lexical Diversity: 2.51613
- Patent Class: 455.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15045043', '13702385', '15069617', '10863642', '10862930']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6974836597612079
- 35 USC 102 Novelty (BERT): 0.4753112714192499
- Combined Prediction Score: 0.6752664209270121
- Mean Citation Score: 159.24431999999996
- Max Citation Score: 163.66965
- Similarity Product: 114.51567352929708

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

Dataset: test