| CODE | ICS2230 | |||||||||
| TITLE | Web Intelligence | |||||||||
| UM LEVEL | 02 - Years 2, 3 in Modular Undergraduate Course | |||||||||
| MQF LEVEL | Not Applicable | |||||||||
| ECTS CREDITS | 6 | |||||||||
| DEPARTMENT | Artificial Intelligence | |||||||||
| DESCRIPTION | The Internet is an evolving medium of information, social interactions, communication, entertainment, commerce, politics, medicine and science. The challenges to address such a huge, evolving network require the use of approaches which are grounded in a solid mathematical background and home to different areas of research. This study-unit will introduce the fundamental concepts and technologies underlying the Web. It will provide the necessary mathematical background behind graphs, probabilistic modeling and data analysis, as well as, practical applications of various techniques, such as text and link analysis, which are important to analyse the content and structure of this evolving distributed space. Study-unit Aims: This study-unit aims to introduce a broad range of methods and techniques that are considered as being fundamental to the development of intelligent applications that seek, exchange, distribute and/or process information found on the World Wide Web. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: • explain the mathematical concepts behind probabilistic modeling and data analysis as applied to the World Wide Web; • describe the principals underpinning Graphs (which include eigenvectors, adjacency matrix, directed networks, degree and paths, power law) in the context of the Web graph; • explain the techniques and fundamental principals central to text analysis as applied to Web content; • explain the techniques and fundamental principals behind link analysis as applied to the analysis of the topological structure of the Web. 2. Skills: By the end of the study-unit the student will be able to: • evaluate and apply specific methods and techniques to analyse the Web's content and structure; • evaluate and apply specific analysis techniques within the development of intelligent web applications. Main Text/s and any supplementary readings: • Modeling the Internet and the Web: Probabilistic Methods and Algorithms by P. Baldi, P.Frasconi and P. Smyth, Published by John Wiley & Sons, Ltd. ISBN: 0-470-84906-1 • Mining the Web: Discovering Knowledge from Hypertext Data, by Soumen Chakrabarti, Morgan Kaufmann Publishers, ISBN: 1-55860-754-4 |
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| STUDY-UNIT TYPE | Lecture, Independent Study & Tutorial | |||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Charlie Abela (Co-ord.) Joel Azzopardi Colin Layfield |
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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.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2023/4. It may be subject to change in subsequent years. |
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