PATENT CLAIM ANALYSIS

Application Number: 15876767
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["706", "012000"]

Abstract:
A system and method for enhanced human/machine workforce management using reinforcement learning, comprising a reinforcement learning server that produces a partially-observable Markov chain model, and an optimization server that uses the partially-observable Markov chain model to select work items and assign them to contact center resources.

Claim (Index 6):
The method of  claim 5 , wherein the plurality of reward values further comprises a plurality of negative rewards, wherein a negative reward is defined as a negative value and the retrain and design server trains away from the reward using negative-reinforcement learning.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 86.0
- Lexical Diversity: 1.36111
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['11743293', '12140846', '15499832', '15859698', '10198102']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3935164817168287
- 35 USC 102 Novelty (BERT): 0.5051008196734308
- Combined Prediction Score: 0.4046749155124889
- Mean Citation Score: 194.977498
- Max Citation Score: 205.9033
- Similarity Product: 116.85500633981228

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

Dataset: test