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Yasser Salem
Yasser Salem
Biography
- Research Interests:
Biography
I am a PhD student at the University College Dublin (UCD), currently working on conversational recommender systems.
I received my Masters degree from the Institute of Technology, Blanchardstown, completing my MSc thesis in April 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. I was a reviewer for the International Arab Conference on Information Technology (ACIT 2008). 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".Publications
Peer-Reviewed Conference Papers
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. [PDF]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. [PDF]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) [PDF]Journal Papers
Y. Salem, A. Hensman and B. Nolan. 2008. Towards Arabic to English Machine Translation. In ITB Journal, May 2008, Issue No. 17: 20-31. [PDF]Book Chapter
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
MSc Thesis
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. [download thesis].
Research
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.
