20 credits at level HE7
Developments in technology have reached a stage where the challenge is no longer confined to the acquisition, processing or transmission of different forms of data. The challenge is in how to handle and process the semantic content of such data. This means that a competent information system designer will need to be aware of all aspects of semantic processing, and all contexts within which it may be used.
Who can benefit:
This module, therefore, would be useful for anyone involved in machine-mediated communication, but would be essential for those involved in information systems development, knowledge-based systems, development of information appliances etc.
To develop a broad and methodical understanding of the wider sense of ‘intelligence’, in relation to knowledge representation and semantic processing.
Appreciate the role of cognitive architectures in making appropriate interpretation of intelligent behaviour, and its relation to modern forms of intelligent agents and knowledge-based information systems.
To develop a basic understanding of the structure of language and its role in communicating information between intelligent agents.
Research and critically evaluate new ideas and proposals in the area of information processing.
The nature of intelligence: perception, higher-level cognitive processing and learning.
Components of intelligent systems: cognitive architecture, language, knowledge and reasoning
Intelligence in humans: visual and auditory perception, memory, thought and language.
Aspects of human communication: speech, gestures and multimodal communication
Natural language processing: lexicon, morphology, syntax, semantics and pragmatics.
Knowledge Representation: propositional knowledge, predicate-argument structure, frame-based systems, scripts.
Reasoning: propositional logic, predicate logic, other logics e.g. descriptive logic
Implementations: knowledge engineering, semantic web, eLearning.
The module will be taught by a combination of lectures and labs. The labs will be based on an appropriate knowledge/language modelling tool and some current standards in knowledge organization e.g. Topic Maps. Lab-based activities will also provide an opportunity for multimodal analysis. In addition, seminars, case studies, directed reading and online research will be used wherever possible.
The first part of the module covers the basics of intelligent systems and knowledge structures, including aspects of human intelligence. This part will be assessed through an investigation-based assignment, where the findings will be documented in a report form.
The second part of the module expands on natural language processing and knowledge representation. In addition to providing a sound foundation of underpinning theoretical principles, ample opportunities will be available for considering implementation issues. Assessment of this part will be managed through a development-based assignment, in which students are expected to develop a system down to coding level.
In addition to the above assignments, quizzes will be administered to make sure that students keep up with the delivery of the module.
NB Where this module is offered online (via BoltOnline) lectures and seminars delivered by Elluminate.
Formal lectures: 20 hours
Lab-based practical work/tutorials: 20 hours
Seminars: 5 hours
Unsupervised practical work: 45 hours
Coursework: 60 hours
Directed reading: 50 hours
Total hours: 200 hours
when you have successfully completed this module you will:
to demonstrate that you have achieved the learning outcome you will:
|1.||Develop a broad and methodical understanding of the wider sense of ‘intelligence’, in relation to data and knowledge structures.||Give a synopsis to describe and discuss the wider scope of ‘intelligence’ in its various contexts.|
|2.||Demonstrate an understanding of the evolution of data-based information systems into the modern form of knowledge-based information systems, particularly in relation to modes of use and application constraints.||Analyse and classify systems and assess their performance according to their data/knowledge handling capability.|
|3.||Understand the structure of language and its role in communicating information between knowledge-based agents.||Demonstrate ability to convert text-based information artefacts into a formal knowledge-based structure in an assignment-based activity.|
|4.||Develop basic natural-language query processing for interrogating knowledge-based information systems.||Follow an appropriate design methodology to create a suitable natural-language interface in an assignment-based activity.|
|5.||Research and critically evaluate new ideas and proposals generated from leading edge development centres.||Demonstrate ability to follow a research methodology to carry out a technical investigation in an assignment-based activity.|
Your achievement of the learning outcomes for this module will be tested as follows:
|Description||Investigation-based Assignment||Development-based Assignment||Interaction with content|
There are no prerequisites for this module.
No restrictions apply.
David E. Rumelhart "Introduction to human information processing" John Whiley and Sons, 1977
John F. Sowa "Knowledge Representation" Brokks/Cole 2000
Daniel Chandler "Semiotics: the basics" Routledge, 2002
Ronald G. Anderson "Information and knowledge based systems, an introduction" Prentice Hall, 1992
Schreiber, G. et.al. "Knowledge engineering and management", MIT Press, 2000
D.Jurafsky and J.H.Martin "Speech and Language Processing" Prentice-Hall, 2000
S. Cori, D. Mandioli and L. Sbatella "the art and craft of computing" Addison Wesley, 1998.
Colin Cherry "On human communication" The MIT Press, 1978
|Host Subject Group:||Computing|
|User Name||Date Accessed||Action|