Personalized recommendation against crowd's popular selection
Information Retrieval
2014-05-14 v4 Social and Information Networks
Physics and Society
Abstract
The problem of personalized recommendation in an ocean of data attracts more and more attention recently. Most traditional researches ignore the popularity of the recommended object, which resulting in low personality and accuracy. In this Letter, we proposed a personalized recommendation method based on weighted object network, punishing the recommended object that is the crowd's popular selection, namely, Anti-popularity index(AP), which can give enhanced personality, accuracy and diversity in contrast to mainstream baselines with a low computational complexity.
Keywords
Cite
@article{arxiv.1403.0353,
title = {Personalized recommendation against crowd's popular selection},
author = {Xuzhen Zhu and Hui Tian and Haifeng Liu and Shimin Cai},
journal= {arXiv preprint arXiv:1403.0353},
year = {2014}
}
Comments
This paper has been withdrawn by the author due to a crucial idea repeatation with "Information filtering via preferential diffusion" published in Physical Review E