mahout overview

 mahout overview

Currently Mahout supports mainly three use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from exisiting categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category.

mahout 包含推荐、分类聚类三种使用场景

Hadoop’s mascot is an elephant

推荐

推荐的应用很广泛，如电子商务、电影、美食、社交等网站

聚类

聚类不那么显而易见，如Google新闻聚类、根据消费者特征聚类

分类

分类像聚类一样普遍存在，如email判断垃圾邮件、文字识别

 

大数据量:mahout + hadoop(map-reduce)

核心思想：集体智慧