1. Introduction to MINDBOT
October 2016

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

3. 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

4. We build CS-based deep learning platform

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

6. 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).

7. 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

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

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

14. MINDSET collaborating with NASA JPL

15. IEEE - to be published in October 2016 IN PRESS

16. We provide very detailed analytics - in real time

17. MINDBOT Platform Demo Video

19. THANK YOU