@inproceedings{wang2010claper,
  abstract = {Classical papers are of great help for beginners to get familiar with a new research area. However, digging them out is a difficult problem. This paper proposes Claper, a novel academic recommendation system based on two proven principles: the Principle of Download Persistence and the Principle of Citation Approaching (we prove them based on real-world datasets). The principle of download persistence indicates that classical papers have few decreasing download frequencies since they were published. The principle of citation approaching indicates that a paper which cites a classical paper is likely to cite citations of that classical paper. Our experimental results based on large-scale real-world datasets illustrate Claper can effectively recommend classical papers of high quality to beginners and thus help them enter their research areas.},
  author = {Wang, Yonggang and Zhai, Ennan and Hu, Jianbin and Chen, Zhong},
  booktitle = {Proceedings of the seventh International Conference on Fuzzy Systems and Knowledge Discovery},
  doi = {10.1109/FSKD.2010.5569227},
  interhash = {7180ddaf1c1765a45fd244027bd0bf43},
  intrahash = {7da72bf2f0538afad9377a0d50c263b4},
  month = aug,
  pages = {2777--2781},
  publisher = {IEEE},
  title = {Claper: Recommend classical papers to beginners},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5569227},
  volume = 6,
  year = 2010
}