Recommender systems, Part 1: Introduction to approaches and algorithms

Most large-scale commercial and social websites recommend options, such
as products or people to connect with, to users. Recommendation engines sort
through massive amounts of data to identify potential user preferences. This
article, the first in a two-part series, explains the ideas behind
recommendation systems and introduces you to the algorithms that power them.
In Part 2, learn about some open source recommendation engines you can put to
work.


Original URL: http://www.ibm.com/developerworks/opensource/library/os-recommender1/index.html?ca=drs-

Original article

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