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MOA - Massive Online Analysis
MOA is a framework for data stream mining. Includes tools for evaluation and a collection of machine learning algorithms. Related to the WEKA project, also written in Java, while scaling to more demanding problems.
06 Nov 09
CEUR-WS.org/Vol-532 - Recommender Systems and the Social Web 2009
Proceedings of the Workshop on Recommender Systems and the Social Web,
collocated with the 3rd ACM Conference on Recommender Systems (RecSys'09),
TechnoCalifornia: The Wisdom of the Few
One of the most common approaches to Recommender Systems is the so-called Collaborative Filtering. The main rationale is the following: In order to predict items that you will like, we find the most similar users to you by looking at your previous likes and dislikes. We then recommend items that those users have liked, but you still don't know.
04 Nov 09
The 13th Machine Learning Summer School
The 13th Machine Learning Summer School was held in Cambridge, UK. This year's edition was organized by the University of Cambridge, Microsoft Research and PASCAL. The school offered an overview of basic and advanced topics in machine learning through theoretical and practical lectures given by leading researchers in the field. We hope to attract international students, young researchers and industry practitioners with a keen interest in machine learning and a strong mathematical background.
02 Nov 09
SPEAR Algorithm - Michael G. Noll
Telling Experts from Spammers: Expertise Ranking in Folksonomies"
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