Howard Rheingold: Collaborative Information Filters

Culture, Knowledge
Howard Rheingodl

Learning Collaborative Information Filters (PDF)

Automating filtering via machine learning is an up-and-coming research category for infotention — Howard ” “Predicting items a user would like on the basis of other users’ ratings for these items has become a well-established strategy adopted by many recommendation services on the Internet. Although this can be seen as a classification problem, algorithms proposed thus far do not draw on results from the machine learning literature. We propose a representation for collaborative filtering tasks that allows the application of virtually any machine learning algorithm. We identify the shortcomings of current collaborative filtering techniques and propose the use of learning algorithms paired with feature extraction techniques that specifically address the limitations of previous approaches.”