PATENT CLAIM ANALYSIS

Application Number: 16053497
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["717", "102000"]

Abstract:
The present invention provides a method for personalizing content and functionality in computer application. The method comprising the steps of: Learning user behavior based on detected input and feature usage by analyzing communication requests and response between client device and application services; Creating product adoption learning model based on user behavior and profile by applying training algorithm of feature usage in relation to user behavior following the feature usage of the user throughout the user lifecycle; Determining feature adoption schedule and time window applying adoption learning model based on user behavior, user profile and feature usage

Claim (Index 12):
The system of  claim 11  wherein the adoption model analyze user a behavior action, after feature usage or content exposure by identifying engagement or adoption actions indicating a successful usage of the application, feature or module.

Metadata:
- Claim Count in Document: 44.0
- Percentile: 96.0
- Lexical Diversity: 1.74138
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15381637', '14828150', '15064344', '13903343', '15394729']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3952472516775352
- 35 USC 102 Novelty (BERT): 0.4949480640508247
- Combined Prediction Score: 0.4052173329148641
- Mean Citation Score: 168.11399799999995
- Max Citation Score: 169.51869
- Similarity Product: 116.8649247994852

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