COMP40080 Knowledge-based Techniques for Industrial Systems

Academic Year 2021/2022

An intelligent system can be characterised by what it knows: that is, what it knows about a domain, and what it knows how to do in that domain. Knowledge has always defined the scope and limits of an intelligent system, and the representation of knowledge -- in combination with computational techniques for exploiting different representations -- has long been a foundational aspect of intelligent system design.

This course will explore knowledge-based techniques for the development of intelligent, knowledge-based systems. We will consider structured knowledge, semi-structured information and unstructured data, and examine the approaches most appropriate to each. The course will span information indexing and retrieval; semantic networks, taxonomies, and ontologies; knowledge sharing, interchange and publishing; XML and XMLS; RDF and RDFS; OWL and the Semantic Web; tools for building and exploiting these approaches; and semantic technologies construed more broadly.These knowledge-based technologies will be placed in their proper context, against the accelerating pace of innovation with more-data-intensive approaches to building intelligent systems.

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Curricular information is subject to change

Learning Outcomes:

On successful completion of this module, a student should be able to:- apply knowledge-based techniques appropriately- build a working representation for a given domain of knowledge- appreciate the industrial uses of these techniques- synthesise an understanding of knowledge-based techniques with previous experience in industry, or in other areas of Computer Science.

Indicative Module Content:

Levels of organisation: data, information, knowledge;
declarative versus procedural knowledge;
the history of knowledge representation;
XML, XMLS;
RDF, RDFS;
OWL and other Semantic Web technologies;

Student Effort Hours: 
Student Effort Type Hours
Autonomous Student Learning

140

Lectures

24

Practical

36

Total

200

Approaches to Teaching and Learning:
in lecture discussion and presentation of course materials. Worked examples; in-class problems; a substantial project that requires the codification and application of knowledge in a particular task domain 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Project: A substantial project to be undertaken by the student on an individual basis. Week 12 n/a Graded Yes

100


Carry forward of passed components
Yes
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 

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