Last modified: 28 Jun 2018 10:27
"Adaptation"
in Computing Science refers to the process by which systems modify their
behaviour based on the user and environment. At the core of this course is a
collection of influential representations and algorithms for modelling users
and the environment to enable adaptation. The course will cover algorithms for
Recommender Systems, used to personalise product recommendations, and for
Personalised Information Retrieval, used to deliver search results personalised
for users and their context. The course will also cover current and future
ideas for adaptive systems, such as Ambient Intelligence, where similar
techniques are integrated into the real world using sensor networks.
| Study Type | Undergraduate | Level | 3 |
|---|---|---|---|
| Session | First Sub Session | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | None. | Sustained Study | No |
| Co-ordinators |
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Information on contact teaching time is available from the course guide.
1st Attempt: 1 two-hour written examination (75%); continuous assessment (25%).
Resit: 1 two-hour written examination (75%); continuous assessment mark carried forward (25%).
During lectures, the Personal Response System and/or other ways of student interaction will be used for formative assessment. Additionally, practical sessions will provide students with practice opportunities and formative assessment.
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