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Introduction to MINDBOT October 2016

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Introduction to MINDBOTOctober 2016

Agenda for today● Technology intro● Demo Video● Execution timeline● QnA

WHY MINDBOT for Customer Support● MINDBOT for 1st level screening to reduce call volume● MINDBOT for 24 hour customer support● MINDBOT will classify which type of CS request and response accuracy - real

time

We build CS-based deep learning platform

Unsupervised text categorization

The purpose is to learn two kinds of text and categorize them from existing data without any supervision.

Transform text into multi-dimensional vector matrix

A customer inquiry is transformed into 2,190-dimensional vector. Now we can categorize them using Convolutional Neural Network (CNN).

66.3% inquiries were correctly answered automatically by AI

Among total 1,356 inquiries, we successfully classified and answered 899 cases fully automatically. Note that we only have limited size of data.

Multidimensional text visualization계정 결제

Training accuracy increased to over 90% when we apply proper NN model

We are able to classify 93% accuracy w/1 month data

MINDSET collaborating with NASA JPL

IEEE - to be published in October 2016 IN PRESS

We provide very detailed analytics - in real time

MINDBOT Platform Demo Video

THANK YOU