This thesis proposes the design, development and evaluation of a hybrid video
recommendation system. The proposed hybrid video recommendation system is based
on a graph algorithm called Adsorption. Adsorption is a collaborative filtering algorithm
in which relations between users are used to make recommendations. Adsorption is used
to generate the base recommendation list. In order to overcome the problems that occur
in pure collaborative system, content based filtering is injected. Content based filtering
uses the idea of suggesting similar items that matches user preferences. In order to use
content based filtering, first, the base recommendation list is updated by removing weak
recommendations. Following this, item similarities of the remaining list are calculated
and new items are inserted to form the final recommendations. Thus, collaborative
recommendations are empowered considering item similarities. Therefore, the
developed hybrid system combines both collaborative and content based approaches to
produce more effective suggestions.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12612624/index.pdf |
| Date | 01 September 2010 |
| Creators | Ozturk, Gizem |
| Contributors | Kesim Cicekli, Nihan |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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