10- https://doi.org/10.1093/ietisy/e88-d.5.1072
An Improved Neighbor Selection Algorithm in Collaborative Filtering
- May 1, 2005
- IEICE Transactions on Information and Systems
- T.-H Kim
Abstract
Nowadays, customers spend much time and effort in finding the best suitable goods since more and more information is placed on-line. To save their time and effort in searching the goods they want, a customized recommender system is required. In this paper we present an improved neighbor selection algorithm that exploits a graph approach. The graph approach allows us to exploit the transitivity of similarities. The algorithm searches more efficiently for set of influential customers with respect to a given customer. We compare the proposed recommendation algorithm with other neighbor selection methods. The experimental results show that the proposed algorithm outperforms other methods.
- # Neighbor Selection Methods
- # Neighbor Selection
- # Graph Approach
- # Algorithm Searches
- # Collaborative Filtering
- # Set Of Customers
- # Neighbor Selection Algorithm
- # Influential Customers
- # Recommendation Algorithm
- # Recommender System
