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 5):
A method for enhanced human/machine workforce management using reinforcement learning, comprising the steps of:\n receiving, at a retrain and design server comprising at least a plurality of programming instructions stored in a memory and operating on a processor of a computing device, a plurality of historical data from a contact center; defining a plurality of reward values to direct the operation of a reinforcement learning server; providing at least a portion of the historical data to a reinforcement learning server for use in a partially-observable Markov chain model; forming, using a reinforcement learning server, a partially-observable Markov chain model based at least in part on the historical data; selecting, using an optimization server, a plurality of work tasks based at least in part on the partially-observable Markov chain model; selecting a plurality of contact center resources; assigning each of the selected work tasks to at least one of the plurality of contact center resources; training a Markov decision process model based at least in part on the partially-observable Markov chain model, using at least a portion of the defined reward values.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 86.0
- Lexical Diversity: 1.36111
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['11743293', '12140846', '15499832', '15859698', '10198102']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3698785733734669
- 35 USC 102 Novelty (BERT): 0.4839859388048341
- Combined Prediction Score: 0.3812893099166037
- Mean Citation Score: 194.977498
- Max Citation Score: 205.9033
- Similarity Product: 146.90527149936557

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

Dataset: test