Lecture Slides
Available on internal web only
- Lecture 1: Introduction [PDF]
- Lecture 2: Term Vocabulary and Postings Lists [PDF]
- Lecture 3: Dictionaries and Tolerant Retrieval [PDF]
- Lecture 4: Index Construction [PDF]
- Lecture 5: Compression [PDF]
- Lecture 6: Scoring and Term Weighting [PDF]
- Lecture 7: The Vector Space Model [PDF]
- Lecture 8: Evaluation and Result Summaries [PDF]
- Lecture 9: Crawling and Web Indexes [PDF]
- Lecture 10: Some Web Basics: Crawl, Index, Classify, Advertise [PDF]
- Lecture 11: Query Expansion [PDF]
- Lecture 12: PageRank [PDF]
- Lecture 13: Crowdsourcing [PDF]
- Lecture 14: Text Classification: Naive Bays [PDF]
- Lecture 15: Text Classification: Vector Classify [PDF]
- Lecture 16: Support Vector Machines and Machine Learning on Documents [PDF]
WhoWhenWhere
- Professor: Eli Upfal
- Professor: Tim Kriska
- HTA: Matt Mahoney
- UTA: David Storch
- GTA: Ahmad Mahmoody
- Spring 2013