| Web Information Search And Management - 12510 - CS 47300 - LE1 |
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Associated Term: Fall 2019
Levels: Undergraduate, Graduate, Professional West Lafayette Campus Lecture Schedule Type Learning Outcomes: See: https://www.cs.purdue.edu/homes/clifton/cs47300/ This course teaches important concepts and knowledge of information retrieval for managing unstructured data such as text data on Web or in emails. At the same time, students will be exposed to a large number of important applications. Students in the course will get hands on experience from homework and a course project. The first part of the course focuses on general concepts/techniques such as stemming, indexing, vector space model, and feedback procedure. The second part of the course shows how to apply the set of techniques on different applications such as Web search, text categorization, and information recommendation. Required Materials: The basic text for this course is: B. Croft, D. Metzler, and T. Strohman, Search Engines: Information Retrieval in Practice, Pearson, 2010. http://ciir.cs.umass.edu/downloads/SEIRiP.pdf The following book may also be of interest, as it gives a somewhat different treatment of the material. You don't need both books, this should be considered optional reading. C. Manning, P. Raghavan, and H. Schüze, Introduction to Information Retrieval, Cambridge University Press (2008). https://nlp.stanford.edu/IR-book/ Technical Requirements: The formal prerequisite is CS 25100: Data Structures and Algorithms (or ECE 36800). It will help if you have taken CS37300: Data Mining and Machine Learning and/or a statistics course such as STAT 35000: Introduction to Statistics or STAT 51100: Statistical Methods. (If you have comparable courses, such as ECE 36800, please contact the instructor.) View Catalog Entry
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