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Interfaces Supporting Knowledge Discovery In Data (ISKDD) BSE(Hons) Name: Mark Hollands Id: 13079042 Supervisor: Assoc. Prof. Trevor Dix Project Aims Interface an existing data mining system, Snob, with the internet Enhance the user interface Measure the effectiveness of these interface updates with usability testing. Contents Data Mining The KDD Process User-centered Design Snob-Online Results Conclusion and Further Work Data Mining Data Mining Came to popularity in the early 90s Driven by academic and commercial interest Purpose Low level Data sets High level Knowledge Discovery Knowledge Discovery in Databases Framework to support Data Mining Multi-disciplinary Support the user’s interactions with the DM system. KDD Process 1. 2. 3. 4. 5. 6. 7. Determine the problem to be solved. Creation of the relevant dataset for mining. Pre-processing of the dataset. Modification of the scope of the dataset. Data Mining Analysis of the model against the hypotheses. Acting upon the discovered knowledge. User-centered Design Software development methodology 3 Main Principals : Goals and subsequent actions Empirical measurement of usage of the system. Iterative Design Snob Unix based data mining application Developed in the CSSE school Utilizes the Minimum Message Length (MML) principal Snob-Online Data Mining Environment Web based KDD Focused Snob-Online Architecture Interactivity Flexibility Portability Consistent requirements Users Projects Data Sessions Volatile Requirements Commands Output Results Visualisation XML Interface ggobi Usability Testing Range of Users Specific Test Cases Monitoring usability and knowledge discovery 3 Stage Process Compares basic graphical interface to command line interface. Adds Interpretation to the system. Adds Visualisation to the system. Results Stage 1 Almost all users preferred the graphical interface. 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. Results Stage 2 Interpretation provided a small gain in knowledge discovery for novice users. Experienced users of Snob saw little knowledge discovery gains. Results Stage 3 Visualisation provided a large increase in knowledge discovery Conclusion 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 The portable XML interface is well suited to the data mining domain Further Work Pre-processing stage Potential extension of the system to a generic web interface for interactive linux applications. Standardised XML Data Mining schema