An improved neighbor selection algorithm in collaborative filtering

Taek Hun Kim, Sung Bong Yang

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Nowadays, customers spend much time and effort in finding the best suitable goods since more and more information is placed online. 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.

Original languageEnglish
Pages (from-to)1072-1076
Number of pages5
JournalIEICE Transactions on Information and Systems
Issue number5
Publication statusPublished - 2005

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


Dive into the research topics of 'An improved neighbor selection algorithm in collaborative filtering'. Together they form a unique fingerprint.

Cite this