... 七、决策树（Decision Trees) 八、推荐系统算法(Collaborative Filtering) 九、支持向量机（Support Vector Machine,SVM) ...
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此外，Neo4j还提供了非常快的图形算法、推荐系统和OLAP风格的分析，而这一切在目前的RDBMS系统中都是无法实现的。
This gives secondary effects like very fast graph algos, recommender systems and OLAP-style analytics that are currently not possible with normal RDBMS setups.
此方法的目的在于对推荐系统执行用户调研或者在线评估之前过滤掉性能较差的算法。
The goal of this approach is to filter out algorithms which have poor performance before the recommender system will be evaluated with a user study or online type evaluations.
可能会存在推荐系统潜在可以推荐的项目，但是算法不包括这些项目。
There might be items for which the system can potentially make a recommendation, but the algorithm never suggests those items.
应用推荐