| CODE | ICS3204 | |||||||||
| TITLE | Advanced Web Intelligence | |||||||||
| UM LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | |||||||||
| MQF LEVEL | Not Applicable | |||||||||
| ECTS CREDITS | 6 | |||||||||
| DEPARTMENT | Intelligent Computer Systems | |||||||||
| DESCRIPTION | This study-unit will build over the theoretical and mathematical concepts dealt with in the 2nd year study-unit ICS2205: Web Intelligence. Analyzing such a huge network such as the Web requires mining techniques that are capable of analyzing both the content, the structure and usage of such a huge graph. From a graph perspective, this study-unit will focus on random networks, in particular, scale-free networks and small worlds. Graph layout algorithms used for visualization will also be considered. Some important algorithms, such as mapreduce, associated with big graphs will also be dealt with. The study-unit will provide insight into various Web data pre-processing and cleaning techniques as well as some popular wrapper generation techniques. This study-unit will further consider some Web-usage mining techniques for the automatic discovery and analysis of patterns in Web usage logs. The increase in popularity of social networks and online web communities present interesting opportunities for the application of different analysis techniques. In this study-unit we will focus on sentiment-analysis and opinion mining techniques as well as some information extraction techniques to mine notable social networks. Furthermore, initiatives such as the Semantic Web are complimenting the Web with meta-data that can be exploited by intelligent systems to provide for more personalized search and visualization. The study-unit will deal with linked open-data, and various linked-data languages, used for the representation and querying of structured data. Study-unit Aims: This study-unit aims to build over the theory and techniques introduced in ICS2205 and to present a broad range of methods and techniques that deal with the evolving, structure, content, usage, semantics and social aspects of the Web. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Describe the principals underpinning graph and link analysis in the context of the Web graph; - Explain the techniques and fundamental principals central to social network analysis; - Explain the techniques and fundamental principals behind semantic web and linked data technologies; - Explain the fundamental techniques associated with web mining and web usage mining. 2. Skills: By the end of the study-unit the student will be able to: - Evaluate and apply specific methods and techniques to analyze the Web's content,structure, usage, semantics and social aspects; - Evaluate and apply specific analysis techniques within the development of intelligent web applications. Main Text/s and any supplementary readings: Main Texts: - Advanced Techniques in Web Intelligence, Juan D. Velasquez, Lakhmi C. Jain, Springer, 2010. ISBN: 978-3-642-14461-5. - Web Data Mining, Bing Liu, Springer, 2011. ISBN: 978-3-642-19459-7. - Networks: An Introduction, Mark Newman, Oxford University Press, May 2010. ISBN-10: 0199206651. Supplementary Readings: - Foundations of Semantic Web Technologies, Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph, Chapman & Hall/CRC, 2009. ISBN: 9781420090505. |
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| RULES/CONDITIONS | Before TAKING THIS UNIT YOU MUST TAKE ICS2205 | |||||||||
| STUDY-UNIT TYPE | Lecture, Independent Study & Tutorial | |||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Charlie Abela Joel Azzopardi |
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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 2025/6. It may be subject to change in subsequent years. |
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