Readings

Books for class reading

• Data Mining and Business Analytics with R, Johannes Ledolter, Wiley, 2013, ISBN: 978-1118447147 (primary book, hereafter referred as "DMR")
• Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (2nd ed.), Bing Liu, Springer, 2011, ISBN: 978-3642194597 (available online) (secondary book, hereafter referred as "WDM")
• Practical Data Science with R, Nina Zumel and John Mount, Manning Publications 2014, ISBN: 9781617291562 (online access via Pitt network) (third book, hereafter referred as "DSR")

Recommended books for further reading

• Machine Learning for Hackers, Drew Conway and John Myles White, O'Reilly, 2012, ISBN: 978-1449303716
• Introduction to Information Retrieval, Manning et al., Cambridge University Press., 2008, ISBN: 0521865719 (PDF available online)
• Data Mining and Analysis: Foundations and Algorithms, Mohammed Zaki and Wagner Meira Jr., Cambridge University Press, 2014, ISBN: 9780521766333 (PDF available online)
• Data Mining: Concepts and Techniques (3rd ed.), Han et al.,Morgan Kaufmann, 2011, ISBN: 978-0123814791
• Mining the Web: Discovering Knowledge from Hypertext Data, Soumen Chakrabarti, Morgan-Kaufmann, 2002, ISBN-13: 978-1558607545
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.), Hastie et al., Springer, 2009, ISBN: 978-0387848570 (PDF available online)
• Introduction to Machine Learning (2nd ed.), Ethem Alpaydin, The MIT Press, 2009, ISBN: 978-0262012430
• Pattern Recognition and Machine Learning, Chris Bishop, Springer, 2007, ISBN: 978-0387310732
• Machine Learning, Tom Mitchell, McGraw Hill, 1997, ISBN: 978-0070428072

Reference materials for R

• R Cookbook, Paul Teetor, O'Reilly, 2011, ISBN: 0-596-80915-8
• R in Action (2nd ed.), Robert Kabacoff, Manning Publications Co., 2013, ISBN: 978-1617291388
• R in a Nutshell (2nd ed.), Joseph Adler, O'Reilly, 2012, ISBN: 978-1449312084
• The R Inferno (2nd ed.), Patrick Burns, ISBN: 9781471046520 (PDF available online)
• Data Mining with R: Learning with Case Studies, Luis Torgo, CRC Press, 2010, ISBN: 978-1439810187
• other online resources

Articles (and more to come)

• From Data Mining to Knowledge Discovery in Databases
• Top 10 Algorithms in Data Mining
• A Tutorial on Principal Component Analysis
• Learning to Link with Wikipedia
• Autonomously semantifying wikipedia
• Private traits and attributes are predictable from digital records of human behavior
• Predicting consumer behavior with Web search
• Demographic Diversity on the Web
• Yes We Can (Profile You): A Brief Primer on Campaigns and Political Data
• For Sale: The American Voter
• The Learning Behind Gmail Priority Inbox
• Democrats, republicans and starbucks afficionados: user classification in twitter
• You Are What You Tweet: Analyzing Twitter for Public Health
• A robust and scalable framework for detecting self-reported illness from twitter
• Predicting the Political Alignment of Twitter Users
• Unfolding the event landscape on twitter: classification and exploration of user categories
• Sentiment analysis of Twitter data
• Cluster-Based Landmark and Event Detection for Tagged Photo Collections
• Model-Based Clustering and Visualization of Navigation Patterns on a Web Site
• Probabilistic topic models
• Document clustering based on non-negative matrix factorization
• Review of statistical network analysis: models, algorithms, and software
• Community structure in social and biological networks
• Recipe recommendation using ingredient networks
• Zipf, Power-laws, and Pareto - a ranking tutorial
• Matrix Factorization Techniques for Recommender Systems
• Amazon.com recommendations: item-to-item collaborative filtering