Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Enformatik Enstitüsü, Bilişim Sistemleri Anabilim Dalı, Türkiye
Tezin Onay Tarihi: 2013
Öğrenci: TUNA HACALOĞLU
Danışman: SEVGİ ÖZKAN YILDIRIM
Özet:Web based customer recommendation systems are being used to provide customized information to the users. They are applied in many areas such as web browsing, information filtering, news or movie recommendation, and e-commerce. The primary aim is to offer suggestions about products or services that users might be interested in. They are intelligent applications to assist users in a decision-making process where they want to choose one item amongst a potentially large set of alternative products or services. These systems are based on information filtering. There are various types of information filtering methods that are used in these systems such as collaborative filtering, content-based filtering and hybrid methods. These types diverge according to the data that they focus on. For example some of them focus on finding similar items where others focus on similar customers. The key component of all recommendation systems is the user model which contains knowledge about the user’s choices, preferences, and past activities which determine his behavior, in other words, his activities on the web. The recommendation systems working mechanism can be summarized in two steps: user model construction and recommendation generation. In this study, a prediction method is proposed according to the structure of the customer spectrum. Considering demographic data of users such as gender, age, education and occupation, the movie genre choice of the users is predicted. A comparison of two different methods will be given in the study on the online raw data provided by an online shopping site.