Literature Review AssignmentReview due date: 1 May, 2017.Selection of topic/area/theme of review by: 20 March, 2017.Submission instructions: Submit via moodle.You are asked to write a Literature Review on a specific topic within one area of a Computer Science specialization that you are interested in (see example below on topic/CS area). Your review will be written in the form of a research paper according to the IEEE conference style format which can be found in: http://www.ieee.org/conferences_events/conferences… for Word and Latex.The paper should be a minimum of 5 pages in the above format. (Latex is strongly recommended).Instructions and advice: Identify an area of specialization that you are interested in. Scan through all available sources to identify interesting, current research on a specific topic within the area. Students opting for the thesis option for their MSc, can use this literature survey to perform introductory-background work for their thesis. After you have done some initial investigation, consult with a faculty member, who specializes in the area you are interested in. (If you do not know who to consult for a specific specialization/topic, ask me and I will advise you on who to contact). With the help of the faculty member, you will clearly identify the topic and title of your review, as well as 3-4 relevant, recent journal or conference papers from where start. Once you finalize the topic and theme of your review, submit them to me by March, 20 (as stated above), in order to have the review proposal approved. Your review must include at least 8-10 papers published in refereed journals and conferences. Your review should be organized thematically (see slides on Writing Research Papers, section on Literature Review). You do not report on each paper you read one by one. Your review is not a summary of studies, but a synthesis of information which requires comparingthemes, methods and conclusions among the different works. A good way of keeping track of all this work and organizing your review is with the use of a synthesis matrix (literature review matrix).An example of such a matrix is shown below. This matrix is taken from the survey paper:“Toward the Next Generation of Recommender Systems: A survey of the state-of-the-art and possible extensions”, by G. Adomavicius in IEEE Transactions on Knowledge and Data Engineering, 17 (6), 2005. (I uploaded it on moodle).This survey is on Recommender Systems, which is a topic of Machine Learning (and Data Mining) which falls under the general area of Artificial Intelligence. The matrix shows how Recommender Systems can be categorized as: 1) content-based, collaborative or hybrid, based on the recommender approach used (rows) and 2) heuristic-based or model-based, based on the types of recommendation techniques used for the rating estimation (columns).On moodle you will also find another two survey papers. I strongly recommend that you go through these survey papers to get an idea of the structure of literature surveys and how they are organized (they also include literature matrices).
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COMP-500 Research Seminars and Methodology
Instructor: Dr. Athena Stassopoulou
Literature Review Assignment
Review due date: 1 May, 2017.
Selection of topic/area/theme of review by: 20 March, 2017.
Submission instructions: Submit via moodle.
You are asked to write a Literature Review on a specific topic within one area of a Computer
Science specialization that you are interested in (see example below on topic/CS area). Your
review will be written in the form of a research paper according to the IEEE conference style
format which can be found in:
http://www.ieee.org/conferences_events/conferences/publishing/templates.html for Word and
Latex.
The paper should be a minimum of 5 pages in the above format. (Latex is strongly
recommended).
Instructions and advice:
1) Identify an area of specialization that you are interested in. Scan through all available
sources to identify interesting, current research on a specific topic within the area. Students
opting for the thesis option for their MSc, can use this literature survey to perform
introductory-background work for their thesis.
2) After you have done some initial investigation, consult with a faculty member, who
specializes in the area you are interested in. (If you do not know who to consult for a
specific specialization/topic, ask me and I will advise you on who to contact).
3) With the help of the faculty member, you will clearly identify the topic and title of your
review, as well as 3-4 relevant, recent journal or conference papers from where start.
4) Once you finalize the topic and theme of your review, submit them to me by March, 20 (as
stated above), in order to have the review proposal approved.
5) Your review must include at least 8-10 papers published in refereed journals and
conferences.
6) Your review should be organized thematically (see slides on Writing Research Papers,
section on Literature Review). You do not report on each paper you read one by one. Your
review is not a summary of studies, but a synthesis of information which requires comparing
COMP-500 Research Seminars and Methodology
Instructor: Dr. Athena Stassopoulou
themes, methods and conclusions among the different works. A good way of keeping track
of all this work and organizing your review is with the use of a synthesis matrix (literature
review matrix).
An example of such a matrix is shown below. This matrix is taken from the survey paper:
“Toward the Next Generation of Recommender Systems: A survey of the state-of-the-art and
possible extensions”, by G. Adomavicius in IEEE Transactions on Knowledge and Data
Engineering, 17 (6), 2005. (I uploaded it on moodle).
COMP-500 Research Seminars and Methodology
Instructor: Dr. Athena Stassopoulou
This survey is on Recommender Systems, which is a topic of Machine Learning (and Data
Mining) which falls under the general area of Artificial Intelligence. The matrix shows how
Recommender Systems can be categorized as: 1) content-based, collaborative or hybrid, based
on the recommender approach used (rows) and 2) heuristic-based or model-based, based on the
types of recommendation techniques used for the rating estimation (columns).
On moodle you will also find another two survey papers. I strongly recommend that you go
through these survey papers to get an idea of the structure of literature surveys and how they are
organized (they also include literature matrices).

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