CSU44D02 – Knowledge Engineering

Module CodeCSU44D02
Module Name Knowledge Engineering
ECTS Weighting [1]5 ECTS
Semester TaughtSemester 2
Module Coordinator/s  Prof. Owen Conlan

Module Learning Outcomes

On successful completion of this module, students will be able to:

  1. Understand the structure of, and apply advanced manipulation techniques to, XML documents;
  2. Develop skills in managing knowledge using Ontological and Semantic Web technologies;
  3. Design and develop Ontologies;
  4. Understand and Compare different Information Retrieval techniques, specifically those used on the web.

Module Content

Knowledge Engineering is a one semester module. It introduces knowledge engineering techniques such as information organization and storage, information retrieval, XML and ontological reasoning. It addresses techniques and technologies for organizing, structuring and storing data, with a view to applying knowledge engineering approaches. Specifically, this module includes advanced Knowledge Management approaches, such as Information Retrieval (IR) and Data Mining, and technologies, such as advanced XML and ontologies.

The objectives this module are to give students an understanding of the organization and manipulation of knowledge and data using a variety of techniques. The main topics covered are:

  • Knowledge Management;
  • Advanced XML;
  • XSLT; XPath; XQuery; XUpdate;
  • Ontologies;
  • OWL; Reasoning;
  • Application in Semantic Web;
  • Artificial Intelligence;
  • Rule-based systems; Case-based reasoning; Bayesian Networks;
  • Retrieving textual information;
  • IR vs database retrieval;
  • Classic IR models (boolean, vector space, probabilistic);
  • Retrieval effectiveness – precision and recall;
  • Information retrieval on the web;
  • First generation search engines;
  • The HITS algorithm;
  • Google; Scamming Google;
  • The next generation of search engines.

Teaching and Learning Methods

This module is delivered through three lectures and one tutorial per week.

Assessment Details

Assessment ComponentBrief Description Learning Outcomes Addressed% of TotalWeek SetWeek Due
Take Home AssignmentAssignment should require no more than 6 hours effort to complete.LO1, LO2, LO3, LO4100%812

Reassessment Details

Take home assignment.

Contact Hours and Indicative Student Workload

Contact Hours (scheduled hours per student over full module), broken down by: 44 hours
Lecture33 hours
Laboratory0 hours
Tutorial or seminar11 hours
Other0 hours
Independent study (outside scheduled contact hours), broken down by:72  hours
Preparation for classes and review of material (including preparation for examination, if applicable)36 hours
Completion of assessments (including examination, if applicable)36 hours
Total Hours116 hours

Recommended Reading List

Links to online material provided during module delivery.

Module Pre-requisites

Prerequisite modules: N/A

Other/alternative non-module prerequisites: e.g. programming languages, specified topics, etc. This information will be particularly relevant for visiting students or students taking this module as an approved module (if applicable).

Module Co-requisites

N/A

Module Website

Blackboard

[1] TEP Glossary

[2] TEP Guidelines on Workload and Assessment