PhD research

RSS (really simple syndication, rich site summary or RDF site summary) is a dialect of XML that provides a method of syndicating on-line content, where postings consist of frequently updated news items, blog entries and multimedia. RSS feeds, produced by organisations or individuals, are often aggregated, and delivered to users for consumption via readers. The semi-structured format of RSS also allows the delivery/exchange of machine-readable content between different platforms and systems.

Articles on web pages frequently include icons that represent social media services which facilitate social data. Amongst these, RSS feeds deliver data which is typically presented in the journalistic style of headline, story and snapshot(s). Consequently, applications and academic research have employed RSS on this basis. Therefore, within the context of social media, the question arises: can the social function, i.e. utility, of RSS be enhanced by producing from it data which is actionable and effective?

Research work for my PhD was based upon the hypothesis that the fluctuations in the keyword frequencies present in RSS can be mined to produce actionable and effective data, to enhance the technology's social utility. To this end, my thesis presented a series of laboratory-based case studies which demonstrated two novel and logically consistent RSS-mining paradigms. The first paradigm allowed users to define mining rules to mine data from feeds. The second paradigm employed a semi-automated classification of feeds and correlated this with sentiment. The outputs produced by the case studies for these paradigms were visualised in order to benefit users in real-world scenarios, varying from statistics and trend analysis to mining financial and sporting data.

Moreover, this work enabled the demonstration of the proof of concept of these paradigms, through the integration of an array of open-source, third-party products into a coherent and innovative, alpha-version prototype software implemented in a Java JSP/servlet-based web application architecture.

My main supervisor was Prof. Mark Levene. My second supervisor was Prof. George Loizou. For insight, support and playing the role of devil's advocate, I am also grateful to Prof. Dell Zhang.


Publications


Teaching

At Birkbeck, as an Associate Lecturer, I currently present courses in:

As Visiting Lecturer, I also present courses at City, London University in:

Between 2008 and 2011, I worked as a Teaching Assistant at Birkbeck responsible for an array of BSc and MSc modules covering programming languages and concepts such as Java, UML, object oriented programming and design, search engines and web technologies, problem solving and databases.

I have also worked on the ProCeSS project under the leadership of Dr. Julia Stegemann.


Education and work experience

I completed an MSc Advanced Information Systems at the Department of Computer Science and Information Systems, Birkbeck College, University of London during 2006 - 2007.

Before this, I was employed as an analyst/programmer for various companies writing software for the Windows PC and IBM AS400 mid-range platforms to extend and develop financial and retail business systems. These roles required extensive liaison with project managers, business analysts and end users throughout the software development cycle to translate requirements into working systems.

In 1998, I obtained a BSc Computer Science from the University of North London, now London Metropolitan University.


Contact

Email:  martin@dcs.bbk.ac.uk.

Postal address:
Department of Computer Science and Information Systems
Birkbeck, University of London
Malet Street
London WC1E 7HX


Other Interests

Foremost amongst my interests is the pen-and-ink drawing of historical buildings and artefacts.