A graph-based core model and a hybrid recommender system for TV users

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2015

Öğrenci: ARDA TAŞCI

Danışman: FEHİME NİHAN ÇİÇEKLİ

Özet:

This thesis proposes a core model to represent user profiles in a graph-based environment which can be the base of different recommender system approaches as well as other cutting edge applications for TV domain. The proposed graph-based core model is explained in detail with node types, properties and edge weight metrics. The capabilities of this core model are described in detail. Moreover, in this thesis, a hybrid recommender system based on this core model is presented with its design, development and evaluation phases. The hybrid recommendation algorithm which takes unique advantages of different types of recommendation system approaches such as collaborative filtering, context-awareness and content-based recommendations, is explained in detail. The introduced core model and the hybrid recommendation system are evaluated and compared with a baseline recommender system and the results are presented. The evaluation results show that the core model and the recommender system presented in this work produce remarkable results for TV domain.