Matan, Ofer
Staff Scheduling for Inbound Call and Customer Contact Centers
Fukunaga, Alex, Hamilton, Ed, Fama, Jason, Andre, David, Matan, Ofer, Nourbakhsh, Illah
The staff scheduling problem is a critical problem in the call center (or, more generally, customer contact center) industry. This article describes DIRECTOR, a staff scheduling system for contact centers. DIRECTOR is a constraint-based system that uses AI search techniques to generate schedules that satisfy and optimize a wide range of constraints and service-quality metrics. DIRECTOR has successfully been deployed at more than 800 contact centers, with significant measurable benefits, some of which are documented in case studies included in this article.
Staff Scheduling for Inbound Call and Customer Contact Centers
Fukunaga, Alex, Hamilton, Ed, Fama, Jason, Andre, David, Matan, Ofer, Nourbakhsh, Illah
The staff scheduling problem is a critical problem in the call center (or, more generally, customer contact center) industry. This article describes DIRECTOR, a staff scheduling system for contact centers. DIRECTOR is a constraint-based system that uses AI search techniques to generate schedules that satisfy and optimize a wide range of constraints and service-quality metrics. DIRECTOR has successfully been deployed at more than 800 contact centers, with significant measurable benefits, some of which are documented in case studies included in this article.
Multi-Digit Recognition Using a Space Displacement Neural Network
Matan, Ofer, Burges, Christopher J. C., LeCun, Yann, Denker, John S.
We present a feed-forward network architecture for recognizing an unconstrained handwritten multi-digit string. This is an extension of previous work on recognizing isolated digits. In this architecture a single digit recognizer is replicated over the input. The output layer of the network is coupled to a Viterbi alignment module that chooses the best interpretation of the input. Training errors are propagated through the Viterbi module.