1. Interfaces Supporting Knowledge Discovery In Data (ISKDD) BSE(Hons) Name: Mark Hollands Id: 13079042 Supervisor: Assoc. Prof. Trevor Dix

2. Project Aims Interface an existing data mining system, Snob, with the internet Interface an existing data mining system, Snob, with the internet Enhance the user interface Enhance the user interface Measure the effectiveness of these interface updates with usability testing. Measure the effectiveness of these interface updates with usability testing.

3. Contents Data Mining Data Mining The KDD Process The KDD Process User-centered Design User-centered Design Snob-Online Snob-Online Results Results Conclusion and Further Work Conclusion and Further Work

4. Data Mining Data Mining Data Mining Came to popularity in the early 90s Came to popularity in the early 90s Driven by academic and commercial interest Driven by academic and commercial interest Purpose Purpose Low level Data sets Low level Data sets High level Knowledge Discovery High level Knowledge Discovery

5. Knowledge Discovery in Databases Framework to support Data Mining Framework to support Data Mining Multi-disciplinary Multi-disciplinary Support the user’s interactions with the DM system. Support the user’s interactions with the DM system.

6. KDD Process 1. Determine the problem to be solved. 2. Creation of the relevant dataset for mining. 3. Pre-processing of the dataset. 4. Modification of the scope of the dataset. 5. Data Mining 6. Analysis of the model against the hypotheses. 7. Acting upon the discovered knowledge.

7. User-centered Design Software development methodology Software development methodology 3 Main Principals : 3 Main Principals : Goals and subsequent actions Goals and subsequent actions Empirical measurement of usage of the system. Empirical measurement of usage of the system. Iterative Design Iterative Design

8. Snob Unix based data mining application Unix based data mining application Developed in the CSSE school Developed in the CSSE school Utilizes the Minimum Message Length (MML) principal Utilizes the Minimum Message Length (MML) principal

9. Snob-Online Data Mining Environment Data Mining Environment Web based Web based KDD Focused KDD Focused

10. Snob-Online Architecture Interactivity Interactivity Flexibility Flexibility Portability Portability

11. Consistent requirements Consistent requirements Users Projects Data Sessions Volatile Requirements Volatile Requirements Commands Output Results

13. Visualisation XML Interface XML Interface ggobi ggobi

14. Usability Testing Range of Users Range of Users Specific Test Cases Specific Test Cases Monitoring usability and knowledge discovery Monitoring usability and knowledge discovery 3 Stage Process 3 Stage Process Compares basic graphical interface to command line interface. Compares basic graphical interface to command line interface. Adds Interpretation to the system. Adds Interpretation to the system. Adds Visualisation to the system. Adds Visualisation to the system.

15. Results Stage 1 Stage 1 Almost all users preferred the graphical interface. Almost all users preferred the graphical interface. Most users were capable of using the header to assess their state within the system. Most users were capable of using the header to assess their state within the system. Users with previous Snob experience quickly understood the system control flow. Users with previous Snob experience quickly understood the system control flow.

16. Results Stage 2 Stage 2 Interpretation provided a small gain in knowledge discovery for novice users. Interpretation provided a small gain in knowledge discovery for novice users. Experienced users of Snob saw little knowledge discovery gains. Experienced users of Snob saw little knowledge discovery gains.

17. Results Stage 3 Stage 3 Visualisation provided a large increase in knowledge discovery Visualisation provided a large increase in knowledge discovery

18. Conclusion A KDD Focus can be used to increase the potential usability and knowledge discovery of a data mining system. A KDD Focus can be used to increase the potential usability and knowledge discovery of a data mining system. User-centered Design maps well to KDD development User-centered Design maps well to KDD development The portable XML interface is well suited to the data mining domain The portable XML interface is well suited to the data mining domain

19. Further Work Pre-processing stage Pre-processing stage Potential extension of the system to a generic web interface for interactive linux applications. Potential extension of the system to a generic web interface for interactive linux applications. Standardised XML Data Mining schema Standardised XML Data Mining schema