1. Intelligent HIV/AIDS FAQ Retrieval System Using Neural Networks
Godfrey Mlambo & Yirsaw Ayalew
Department of Computer Science,
University of Botswana
IASTED Health Informatics 2014, Gaborone, Botswana

2. Neural Network Approach
Presentation Outline
Motivation
Challenge ...Mapping
Neural Network Approach
Background
Architecture
Results
Conclusion

3. Artificial Neural Network
FAQs are commonly used mechanisms for providing information
In the area of HIV/AIDS, there are many manual FAQs (e.g., MASA FAQ brochure, IPOLETSE call center manual, etc)
Access to such FAQs can be further strengthened using automated system
Objective: Develop FAQ Retrieval system using Neural Networks

4. Challenge of Mapping ...
Word sense disambiguity, lexico - grammatical content, arbitrary words e.g. What are symptoms of AIDS? What are signs of AIDS?, how do you know indications of AIDS show, How do you know that you have aids?
Many techniques have been used but one promising is artificial neural NN
NN mimics the human brain ability to resolve

5. Artificial Neural Network Approach
Basic unit of a NN.

6. Neural Network Architectures

7. Multilayer Feedforward Layer NN Architecture

8. Neural Network FAQ Retrieval
Backpropagation Training Rule for Mapping/Classification of HIV/AIDS FAQ

9. Designing Neural Network System
Data Transformation …
Feature extraction
Feature selection
Neural Network Architecture:-
Architecture type
Determining input, hidden and output neurons
Heuristic methods
Experimental techniques
Teaching mode & learning rule
Supervised/Unsupervised/Reinforcement
Learning rules
Activation Function

10. Training the NN with HIV/AIDS FAQs

11. Answering HIV/AIDS FAQ

12. Experimental Design MATLAB and simulated using the Neural Network Tool
467 HIV/AIDS FAQ build a Corpus MASA booklet IPOLESTE HIV/AIDS FAQ manual, UN AIDS...
Neural Network Designed and Trained
M(F(FAQn),F(Qm)): [0,1] .... Ranking the Document

13. Experimental Design System subjected 120 unseen HIV/AIDS FAQ
Evaluation done by HIV/AIDS counsellors, Lecturers and students
Recall and Rejection Rate evaluation metrics

14. Sample Page of IHAFR System

15. Evaluation of the IHAFR System

16. Conclusion
Comparison with a keyword-based FAQ retrieval Systems shows a better recall and rejection rate
To enhance performance there i.e. Rejection rate
Need to increase corpus size of HIV/AIDS FAQ
Need to incorporate other information retrieval techniques