Network Science @ Recommender Systems
نویسنده
چکیده
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.
منابع مشابه
Improving Accuracy of Recommender Systems using Social Network Information and Longitudinal Data
The rapid development of technology, the Internet, and the development of electronic commerce have led to the emergence of recommender systems. These systems will assist the users in finding and selecting their desired items. The accuracy of the advice in recommender systems is one of the main challenges of these systems. Regarding the fuzzy systems capabilities in determining the borders of us...
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