Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems.

Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems.

In recent years, recommender systems have become an effective method to process information overload. However, recommendation technology still suffers from many problems. One of the problems is shilling attacks-attackers inject spam user profiles to disturb the list of recommendation items. There ar...

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Bibliographic Details
Main Authors: Min Gao, Renli Tian, Junhao Wen, Qingyu Xiong, Bin Ling, Linda Yang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4534203?pdf=render

Internet

http://europepmc.org/articles/PMC4534203?pdf=render

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