PATENT CLAIM ANALYSIS

Application Number: 15896608
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["463", "023000"]

Abstract:
Embodiments of systems presented herein may perform automatic granular difficulty adjustment. In some embodiments, the difficulty adjustment is undetectable by a user. Further, embodiments of systems disclosed herein can review historical user activity data with respect to one or more video games to generate a game retention prediction model that predicts an indication of an expected duration of game play. The game retention prediction model may be applied to a user's activity data to determine an indication of the user's expected duration of game play. Based on the determined expected duration of game play, the difficulty level of the video game may be automatically adjusted.

Claim (Index 9):
The computer-implemented method of  claim 1 , wherein the plurality of parameter functions are generated using a machine learning algorithm applied to a set of historical data generated by a plurality of users interacting with the video game.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 1.91667
- Patent Class: 463.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15416961', '15445784', '15064115', '15639973', '14848095']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3136800171090433
- 35 USC 102 Novelty (BERT): 0.4858347689701825
- Combined Prediction Score: 0.3308954922951572
- Mean Citation Score: 223.004262
- Max Citation Score: 258.5695
- Similarity Product: 208.02251836156844

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