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 ...
The purpose of this thesis work done at Ericsson Research in Kista was to investigate the possibili...
AbstractIn the area of intelligent systems, research about recommender systems is a critical topic a...
Despite recommender systems based on collaborative fil-tering typically outperform content-based sys...
With the increasing amount of TV programs and the integration of broadcasting and the Internet with ...
In this thesis, it is aimed to design a system which builds user profiles to model users’ preference...
Nowadays, providing tools that eases the interaction of users with websites is a big challenge in e-...
This thesis proposes the design, development and evaluation of a hybrid video recommendation system....
Over the past few years, technology has impacted heavily in the distribution of television content. ...
The task of the recommendation systems is to recommend items that are relevant to the preferences of...
Recommender systems alleviate the problem of searching for interesting content in the iTV do- main ...
Recommender systems are envisioned and design to serve automatic recommendations for various service...
he expansion of Digital Television and the convergence between conventional broadcasting and televis...
The arrival of Digital TV has ensued the growth in the volume of TV programs offered by TV operators...
The expansion of Digital Television and the convergence between conventional broadcasting and televi...
Usually, people will search on the Internet for movie that they want to watch. However, it is tediou...
The purpose of this thesis work done at Ericsson Research in Kista was to investigate the possibili...
AbstractIn the area of intelligent systems, research about recommender systems is a critical topic a...
Despite recommender systems based on collaborative fil-tering typically outperform content-based sys...
With the increasing amount of TV programs and the integration of broadcasting and the Internet with ...
In this thesis, it is aimed to design a system which builds user profiles to model users’ preference...
Nowadays, providing tools that eases the interaction of users with websites is a big challenge in e-...
This thesis proposes the design, development and evaluation of a hybrid video recommendation system....
Over the past few years, technology has impacted heavily in the distribution of television content. ...
The task of the recommendation systems is to recommend items that are relevant to the preferences of...
Recommender systems alleviate the problem of searching for interesting content in the iTV do- main ...
Recommender systems are envisioned and design to serve automatic recommendations for various service...
he expansion of Digital Television and the convergence between conventional broadcasting and televis...
The arrival of Digital TV has ensued the growth in the volume of TV programs offered by TV operators...
The expansion of Digital Television and the convergence between conventional broadcasting and televi...
Usually, people will search on the Internet for movie that they want to watch. However, it is tediou...
The purpose of this thesis work done at Ericsson Research in Kista was to investigate the possibili...
AbstractIn the area of intelligent systems, research about recommender systems is a critical topic a...
Despite recommender systems based on collaborative fil-tering typically outperform content-based sys...