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2011/12 Undergraduate Module Catalogue

COMP3740 Knowledge Management and Adaptive Systems

20 creditsClass Size: 70

Module manager: Dr Eric Atwell

Taught: Semesters 1 & 2 View Timetable

Year running 2011/12


COMP2445Database Applications and Graphics
COMP2540Software Systems Engineering

This module is not approved as an Elective


On completion of this module, students should be able to:

- Understand the nature and importance of organisational knowledge;
- Describe a range of techniques for information retrieval and extraction, and explain their relevance to knowledge management;
- Describe the role of OLAP in the process of knowledge discovery;
- Use appropriate tools in a data mining activity;
- Understand a selection of machine learning algorithms and apply them in a data mining activity;
- Apply appropriate techniques to identify user needs, analyse requirements, design, implement and evaluate user-adaptive systems;
- Describe specified personalisation techniques and apply at least one to a practical problem;
- Understand the potential for and drawbacks of personalisation.


Management of Organisational Knowledge; Techniques for Information Retrieval and Extraction: 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.

User Diversity and Personalisation: Properties of the user modelled; Data about the user collected; Personalisation techniques (e.g. customisation, stereotypes, collaborative filtering and recommendations). Application of adaptive techniques: personalisation for e-commerce, adaptive user interfaces, adaptive support for decision making and group work, individualised e-learning, personalised ubiquitous computing. HCI and user adaptive systems: identifying user needs and obtaining requirements for personalised systems; involving users in design; incremental prototyping; evaluation.Potential for and drawbacks of personalisation and privacy.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Class tests, exams and assessment12.002.00
Class tests, exams and assessment13.003.00
Private study hours151.00
Total Contact hours49.00
Total hours (100hr per 10 credits)200.00

Private study

taught session prep: 36 hours
taught session follow-up: 36 hours
self-directed study: 34 hours
assessment activities: 45 hours

Opportunities for Formative Feedback

Attendance and formative assessment.

Methods of assessment

Exam typeExam duration% of formal assessment
Open Book exam2 hr 00 mins0.00
Open Book exam3 hr 00 mins100.00
Total percentage (Assessment Exams)100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 04/10/2011


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