Modern libraries provide only modest book recommendation services. We present in this paper a novel book evaluation and recommendation approach based on collective intelligence. Inspired by PageRank, this approach evaluates books based on their mutual recommendation relations provided by online bookstores' massive user group, before recommending books from not only one particular category but also relevant categories. The experimental results show that it can provide more comprehensive recommendation which pinpoints a user's expectation.%当前图书馆只能向读者提供非常有限的图书推荐服务.本文提出可采用从网上书店获得的大量公开数据作为推荐参考标准的思路,使推荐不再依赖有限的本地数据,而是基于集体智慧.本文提出一个根据图书关联关系网络来评价图书的内容相关性及推荐价值的方法.初步实验结果表明,这一基于集体智慧的图书推荐方法能做出更全面和满意的图书推荐.
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