  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.
