I am a PhD student at the Queen's University Belfast, currently working on conversational recommender systems with
Dr Jun Hong
I received my Masters degree from the Institute of Technology, Blanchardstown, completing my MSc thesis in 2009,
entitled, "A generic framework for Arabic to English machine translation of simplex sentences using
the Role and Reference Grammar linguistic model". This research was the first contribution using the Role and Reference Grammar (RRG) model
as a basis for machine translation. My MSc thesis is available on the official Role and Reference Grammar website
My advisors were Dr. Brian Nolan and Mr. Arnold Hensman.
While working on my MSc, I published 6 papers and a book chapter.
I was a reviewer for the International Arab Conference on Information Technology (ACIT 2008), and external reviewer for the 15th Asia-Pacific Web Conference (APWeb 2013).
I also delivered an invited talk at Dublin City University (DCU) in July 2008 entitled "UniArab: a universal machine translator system
for Arabic based on Role and Reference Grammar".
Queen's University Belfast (United Kingdom)
PhD, Artificial Intelligence, In Progress.
Recommender systems are a common way to promote products or services that may be of interest to a user, usually based on some profile of interests.
The single-shot approach, which produces a ranked list of recommendations, is limited by design.
It works well when a user’s needs are clear, but it is less suitable when a user’s needs are not well known, or where they are likely to evolve during the course of a session.
In these scenarios it is more appropriate to engage the user in a recommendation dialog so that incremental feedback can be used to refine recommendations.
This type of conversational recommender system is much better suited to help users navigate more complex product spaces.
I am interested in improving the efficiency of recommender systems.
Institute of Technology Blanchardstown (Dublin, Ireland)
MSc, Computational Linguistics, 2007 — 2009
Machine translation is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another.
The main motivation of this research is to provide a proof of concept implementation for translating Arabic into English.
We developed a rule-based lexical framework for Arabic language processing using the Role and Reference Grammar linguistic model.
A system, called UniArab is introduced to support the framework. The UniArab system uses Modern Standard Arabic (MSA) and takes MSA as input in the native orthography, parses the sentence(s) into a logical meta-representation,
and using this, generates a grammatically correct English output. UniArab utilizes an XML-Based implementation of elements of the Role and Reference Grammar theory,
and its representations for the universal logical structure of Arabic sentences.
This research was the first machine translation based on Role and Reference Grammar.
Institute of Technology Blanchardstown (Dublin, Ireland)
Bachelor of Science (Honours) in Computing, 2003 — 2007
I received a B.Sc. (Hons.) in computing with first class honours from the School of Informatics and Engineering at ITB.
During my undergraduate studies, I designed and implemented a new encryption algorithm using technologies such as Java, MD5 and ODBC.
My algorithm is secure, using public and private keys and 256 bit encryption based on XOR. The project applied mathematical thinking of strategies,
in particular algebra and calculus, to the design and creation of the encryption algorithm in software.
The project achieved a prize for the best software project in May 2007.
Peer-Reviewed Conference Papers
Y. Salem and J. Hong, “History-aware critiquing-based conversational recommendation”, in Proceedings of the 22nd international conference companion on World Wide Web (WWW 2013), Rio de Janeiro, Brazil, May 2013.
K. McCarthy, Y. Salem and B. Smyth, “Experience-Based Critiquing: Reusing Critiquing Experiences to Improve Conversational Recommendation”, in Proceedings of the 18th International Conference on Case-Based Reasoning (ICCBR 2010),
Alessandria, Italy, July 2010.
B. Nolan and Y. Salem, “UniArab: An RRG Arabic-to-English Machine Translation Software”, in Proceedings of the 2009 International Conference on Role and Reference Grammar, University of California, Berkeley, USA, August 2009. [PDF]
Y. Salem and B. Nolan, “Designing an XML Lexicon Architecture for Arabic Machine Translation Based on Role and Reference Grammar”, in Proceedings of the 2nd International Conference on Arabic Language Resources and Tools (MEDAR 2009),
Cairo, Egypt, April 2009.
Y. Salem and B. Nolan, “An Arabic-to-English Machine translation system using an XML–based Role and Reference Grammar representation”, abstract accepted for the 23rd Annual Symposium on Arabic Linguistics, University of Wisconsin-Milwaukee, USA, April 2009.
Y. Salem and B. Nolan. 2009. UNIARAB: An Universal Machine Translator System For Arabic Based On Role And Reference Grammar, in Proceedings of the 31st Annual Meeting of the Linguistics Association of Germany (DGfS 2009),
University of Osnabruck, Germany, March 2009. [PDF]
Y. Salem, A. Hensman and B. Nolan, “Implementing Arabic-to-English Machine Translation using the Role and Reference Grammar Linguistic Model” in Proceedings of the Eighth Annual International Conference on Information Technology and Telecommunication (ITT 2008), Galway, Ireland, October 2008.
(Runner-up for Best Paper Award)
Y. Salem, A. Hensman and B. Nolan. 2008. Towards Arabic to English Machine Translation. In ITB Journal, May 2008, Issue No. 17: 20-31.
Nolan, Brian and Yasser Salem, UniArab: RRG Arabic-to-English Machine Translation, In: New Perspectives in Role and Reference Grammar, Watara Nakamura (ed.), London: Cambridge Scholars Publishing, 312-344, December 2011
Y. Salem, "A generic framework for Arabic to English machine translation of simplex sentences using the Role and Reference Grammar linguistic model"
MSc Thesis, ITB, 2009.
You can also view my Google Scholar Citation Profile.