教学大纲：1.Web search overview, Web crawling and indexes2.Boolean retrieval3.The term vocabulary and postings lists4.Dictionaries and tolerant retrieval5.Index construction6.Index compression7.Scoring, term weighting, and the vector space model8.Computing scores in a complete search system9.Evaluation in information retrieval10.Relevance feedback and query expansion11.Probabilistic information retrieval 12.Language models13.Supervised learning 14.Unsupervised learning and semi-supervised learning 15.Matrix factorization16.Graph mining17.Social search and recommender systems

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课程考核要求：1. In class quizzes (30%)2. Homework (30%)3. Final project (40%)

• 教材和参考书：教材：Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze. Introduction to Information Retrieval. Cambridge University Press, 2008. 参考书：1.Bruce Croft, Donald Metzler, and Trevor Strohman. Search Engines: Information Retrieval in Practice. Addison Wesley, 2009. 2.Bing Liu. Web Data Mining: Exploring Hyperlinks, Contents and Usage Data. Springer, 2006.3.Jiawei Han, and Micheline Kamber. Data Mining: Concepts and Techniques. Morgan Kaufmann, Second Edition, 2005. 4.Trevor Hastie, Robert Tibshirani, Jerome Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, Second Edition, 2009.5.Christopher M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.