Study-Unit Description

Study-Unit Description


TITLE Knowledge Discovery and Management

LEVEL 03 - Years 2, 3, 4 in Modular Undergraduate Course


DEPARTMENT Artificial Intelligence

DESCRIPTION Modern organisations are becoming increasingly reliant on discovering and managing knowledge to maintain a competitive advantage. The study-unit Knowledge Representation and Reasoning assumed that knowledge to represent had already been identified. The Web Intelligence and Advanced Web Intelligence study-units investigate the acquisition of knowledge from unstructured textual sources. In this study-unit, we investigate the acquisition and integration of knowledge from multiple diverse sources and strategies for maintaining it.

The ultimate purpose of knowledge acquisition is to analyse multiple diverse data and information sources (which may be textual, numeric, or multimedia, or user behaviour patterns) to discover interesting patterns that can be generalised and represented as knowledge that can be used to assist with human decision making, These techniques can be used in diverse areas such as: automatically learning a natural language grammar and the construction of natural language processing tools; personal, local, national, and global health care; education; smart technologies (e.g. smart homes); financial analysis and planning; recommender systems; personal assistants; knowledge risk identification and management; weather prediction; pollution management; traffic management; knowledge brokerage services; and improving search engine results.

Knowledge management techniques play an essential role in keeping the acquired knowledge up-to-date as mismatches between the knowledge acquired and knowledge in the real-world will lead to incorrect decisions.

Study-unit Aims:

To cover building and using computational tools to analyse huge and/or changing unstructured and diverse data sources (Big Data) to acquire information and knowledge; applying knowledge representation techniques to store and manipulate the information and knowledge; to design and implement systems that can learn new information and knowledge by applying reasoning techniques; and building computational tools to use and manage the information and knowledge acquired and learned. A number of state-of-the-art case studies will also be covered.

Learning Outcomes:

1. Knowledge & Understanding:
By the end of the study-unit the student will be able to:

- Describe mechanisms for acquiring knowledge from diverse data sources;
- Identify probable data sources to be analysed for a given problem;
- Explain the need for knowledge management at a personal, local, organisational, and global level in a select number of application areas.

2. Skills:
By the end of the study-unit the student will be able to:

- Use one or more data mining tools;
- Design and implement a computational tool to acquire knowledge from diverse data sources for a given problem;
- Apply knowledge representation techniques to store and manipulate the acquired information and knowledge;
- Apply reasoning techniques to learn new knowledge;
- Design and build a computational tool to use and manage the acquired and learned information and knowledge.

Main Text/s and any supplementary readings:

- Rajendra Akerkar, Priti Sajja. Knowledge-Based Systems. 2010. Jones & Bartlett Learning
- Richards, Debbie; Kang, Byeong-Ho (Eds.), Knowledge Acquisition: Approaches, Algorithms and Applications. 2009. Springer
- Kimiz Dalkir. Knowledge Management in Theory and Practice. 2005. Elsevier Publishers

Additional material will be provided through the VLE


STUDY-UNIT TYPE Lecture and Independent Study

Assessment Component/s Resit Availability Weighting
Project Yes 100%

LECTURER/S Charles Abela
Joel Azzopardi (Co-ord.)
Jean Paul Ebejer
Adam Gauci
Kristian Guillaumier
Colin Layfield
Alessio Magro
Christopher D. Staff

The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
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Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the study-unit description above applies to the academic year 2017/8, if study-unit is available during this academic year, and may be subject to change in subsequent years.