@inproceedings{988ea51f93944fb68940b744121d79c9,
title = "A collaborative filtering algorithm based on social network information",
abstract = "In traditional collaborative filtering recommendation, the matrix sparsity and cold start restricted the accuracy of system. In this paper, we develop a way to enhance the recommendation effectiveness by merging neighborhood relationship and users keyword of social network information into collaborative filtering. We extend the calculation method of the TOP N neighbors which is the most important from two aspects. Our method expands the information capacity which can be used by collaborative filtering, improves the accuracy of recommendation and eases the cold start problem in recommendation system. We conducts experiment based on KDD 2012 real data set. The result indicates that our algorithm performs more superior than traditional collaborative filtering algorithm.",
keywords = "collaborative filtering, data mining, recommendation system, social network",
author = "Rui Wang and Bailing Wang and Junheng Huang",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd IEEE International Conference on Big Data, Big Data 2015 ; Conference date: 29-10-2015 Through 01-11-2015",
year = "2015",
month = dec,
day = "22",
doi = "10.1109/BigData.2015.7364031",
language = "英语",
series = "Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2384--2389",
editor = "Howard Ho and Ooi, \{Beng Chin\} and Zaki, \{Mohammed J.\} and Xiaohua Hu and Laura Haas and Vipin Kumar and Sudarsan Rachuri and Shipeng Yu and Hsiao, \{Morris Hui-I\} and Jian Li and Feng Luo and Saumyadipta Pyne and Kemafor Ogan",
booktitle = "Proceedings - 2015 IEEE International Conference on Big Data, Big Data 2015",
address = "美国",
}