188/4 E-Commerce Group
Institute of Software Technology and Interactive Systems
Vienna University of Technology
Favoritenstrasse 9-11/188, A-1040 Vienna, Austria

Network Science @ Recommender Systems

L. Grad-Gyenge, H. Werthner
Turku Centre for Computer Science
Effective, Agile and Trusted eServices Co-Creation
67 - 77
Speech with proceedings
Hidden Keywords: 
Department Focus: 
Business Informatics
TU Focus: 
Computational Science and Engineering
ISBN: 978-952-12-2914-5
We present a conceptual approach in the field of recommender systems, which is intended to model human consumption by maintaining a network of heterogeneous nodes and relationships. We think of this model as the reflection of the corresponding cognitive functionality of human thinking, as we maintain a structure which is similar to the structures established by neural networks. To explain our motivation and the proposed structure we are combining the results of recommender systems and network science. We propose a generalized approach that intends to involve concepts from social networks, semantic distance, association rule mining, ontological modeling and expert systems. Our approach will access and integrate different information sources, modeling also additional information types. We expect that our approach will find the importance factors of the aforementioned information sources for the generation of high quality recommendations.
Abstract German: