Mahout's presentation at AlphaCSP's The Edge 2010

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Google knows what you want to search for, Amazon what you want to buy, and Facebook knows who your friends are before you connect to them. Are they reading your minds? the answer is yes.

In this session I'll teach you how to use Mahout, an Apache machine learning library, and read the minds of your users based on the information you have already gathered. And if your dataset is too big, we'll use Hadoop to analyze it on a distributed environment.

http://www.javaedge.com/jedge/abstracts.jsp

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  • למידה חישובית
  • Make it clear that I don’t want the crowd to read the table, it’s only to generate an overwhelming sensation
  • מערכות המלצה
  • Strictly speaking, these are examples of “collaborative filtering” -- producing recommendations based on, and only based on, knowledge of users’ relationships to items. These techniques require no knowledge of the properties of the items themselves. This is, in a way, an advantage. This recommender framework couldn’t care less whether the “items” are books, theme parks, flowers, or even other people, since nothing about their attributes enters into any of the input.
  • UserSimilarity: Way to compare users (user based approach)ItemSimilarity: Way to compare items (items based approach)Recommender: Interface for providing recommendationsUserNeighborhood: Interface for computing a neighborhood of similar users that can then be used by the Recommenders
  • http://www.flickr.com/photos/martinimike/3770274175/http://www.flickr.com/photos/fotoosvanrobin/3182238046/http://www.flickr.com/photos/this_girl_daydreams/3190110968/http://www.flickr.com/photos/19998197@N00/3238445535/
  • Talk aboutRecommenderEvaluator
  • ממוצעסטיית תקן
  • Explain that we are going to take all project dependencies, pack them together with Ant and include them on the package phase of Maven
  • ×