This class was taught at Stanford in Autumn 2008. You can register to watch all 25 CS193H lecture videos through the Stanford Center for Professional Development.
The book has a new Web site www.mmds.org. This page will no longer be maintained. Your browser should be automatically redirected to the new site in 10 seconds. Here are the materials from several past courses on data mining and/or Web mining. From 2003 From 2005 cotaught with Anand Rajaraman. From 2006 cotaught with Anand Rajaraman. From 2008 cotaught with Anand Rajaraman. From 2009 cotaught with
Information retrieval is the process through which a computer system can respond to a user's query for text-based information on a specific topic. IR was one of the first and remains one of the most important problems in the domain of natural language processing (NLP). Web search is the application of information retrieval techniques to the largest corpus of text anywhere — the web — and it is the
Handouts: Basic Math recitation Slides Hadoop session Slides, Example, Hadoop Installation Instructions 1/3/2011 Introduction [PDF], MapReduce [PDF] Reading: Ch2: Large-Scale File Systems and Map-Reduce 1/5/2011 Association Rules: Frequent itemsets and Association rules [PDF] Reading: Ch6: Frequent itemsets 1/10/2011 Near Neighbor Search in High Dimensional Data [PDF] Reading: Ch3: Finding Simila
Handouts: 1/5: Introduction Introduction [slides] [reading] 1/7: MapReduce MapReduce [slides] [reading] 1/12: Recommendation System Recommendation System [slides] [reading] 1/14: Near Neighbor Search in High Dimensional Data Near Neighbor Search in High Dimensional Data [slides] [reading] 1/19: Locality Sensitive Hashing (LSH) Locality Sensitive Hashing (LSH) [slides] [reading] 1/21: Structure of
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