Extending singular value decomposition based recommendation systems with tags and ontology

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Tezin Türü: Yüksek Lisans

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

Tezin Onay Tarihi: 2014

Öğrenci: YAKUP TURGUT

Danışman: İSMAİL HAKKI TOROSLU

Özet:

Due to increase of the volume of data related to user ratings on items, in recent years, recommendation systems became very popular, which uses this data in order to rec- ommend items to users in many different domains. Singular Value Decomposition is one of the most widely studied collaborative filtering recommendation techniques. In some applications users are also allowed to enter (sometimes free) tags in addition to their ratings on items. Adding tags in addition to regular users’ ratings on items have also been studied from different perspectives. In this work, we embedded tags entered by users into SVD technique in a simple but novel way. We also present methods that incorporate ontology to determine relationships between tags into consideration while dealing with movie recommender systems. We have applied our approach on movie recommendation system.