COMP3410
Technologies for Knowledge Management
10 credits

Taught Semester 2 View Timetable

Year running 2005/06

Pre-requisites
COMP2400

This module is not approved as an Elective

Objectives
On completion of this module students should be able to:
* understand the nature and importance of organisational knowledge;
* describe classical information retrieval techniques, and their relevance to knowledge management;
* describe the role of OLAP and data mining tools in the process of knowledge discovery;
* describe a selection of machine learning algorithms and demonstrate use of these in a data mining activity.

Syllabus
Management of Organisational Knowledge; Classical Models of Information Retrieval: Content analysis and representation; Evaluation; File Structures for information retrieval; query broadening. Data Warehousing: Building a data warehouse; data hypercubes and online analytical processing. Data Mining: Basic concepts; process model for data mining, algorithms including, for example, decision tree builders, clustering algorithms and association rule builders.

Teaching methods
Lectures: 20 x 1 hour;
Laboratory sessions: 5 x 1 hour.

Private study
Taught session preparation: 20 hours;
Self-directed study: 30 hours;
Summative assessment: 25 hours.

Progress monitoring
Two pieces of coursework summatively assesssed.

Methods of assessment
Exam: 1 paper, 2 hours, 70%, closed book;
Departmental assessment: 30%:
(2 computer-based exercises assessed by 5-page reports).

Reading list
The reading list is available from the Library website

Last updated: 23/03/2005

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