@article{Baik2001,
        title = {Bidding for a group-specific public-good prize},
        author = {Kyung Hwan Baik and In-Gyu Kim and Sunghyun Na},
        journal = {Journal of Public Economics},
        month = {Dec},
        number = 3,
        pages = {415--429},
        volume = 82,
        year = 2001,
        url = {http://www.sciencedirect.com/science/article/B6V76-44BMCW0-6/1/20b21bdde6f7377eb09e109191aec766},
        biburl = {http://www.bibsonomy.org/bibtex/28d0d1963ae89df90482b5256325e6326/smicha},
	keywords = {Public-good prize}
}

@misc{narayanan-2006,
        title = {How To Break Anonymity of the Netflix Prize Dataset},
        author = {Arvind Narayanan and Vitaly Shmatikov},
        year = 2006,
        url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0610105},
        description = {[cs/0610105] How To Break Anonymity of the Netflix Prize Dataset},
	abstract = { We present a new class of statistical de-anonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. Our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge.},
	biburl = {http://www.bibsonomy.org/bibtex/286b686a7fad55fa225123b2f79de87a8/hotho},
	keywords = {prize Preis dataset anonymity recommender netflix}
}