CS5604 - Information Retrieval - Fall 2019

Alternate title: Search Engines and Text Mining with Big Data

Alternate title: Applied Machine Learning (Underlying Google)

Why take CS5604?

• To prepare you for working at Google, Microsoft, or any company involved in machine learning, text analytics, searching, and/or WWW.
• To prepare you for research involving search engines, natural language processing, text mining, classification, clustering, indexing, recommendation/personalization, information extraction/seeking/exploration, social media, and/or web archiving.
• To gain proficiency with parallel processing on clusters with big data nodes.

Resources

• 20+ node Hadoop Cluster with 10Gbit network connection
• Cloudera software including HBase, HDFS, Hive, Mahout, MapReduce, Nutch, Pig, Solr, Spark, Sqoop`
• MeTA, NLTK, and Python toolkits

References

• Textbook: Introduction to Information Retrieval by Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze. 2008, 496 pages, Cambridge University Press, ISBN-10: 0521865719, ISBN-13: 978-0521865715. See also online versions, slides, etc.
• Free (through Library download), recommended: ChengXiang Zhai and Sean Massung. 2016. Text Data Management and Analysis: a Practical Introduction to Information Retrieval and Text Mining. Association for Computing Machinery and Morgan & Claypool, New York, NY, USA.
• VTechWorks reports from CS5604 projects

Course Organization

• CS5604 Fall 2019 class: CRN 82915, TR, 3:30-4:45pm, McB 231, 15T
• Approach: problem/project based learning, flipped classroom
• Goal: solve the following question: How can we best build a state-of-the-art information retrieval and analysis system in support of the communities interested in each of
  1. All the nation's electronic theses/dissertations (ETDs) - related to an IMLS grant to VT and ODU for 8/1/2019 - 7/31/2022
  2. Big business and the addiction crisis (starting with 14M documents related to tobacco companies and legal suits)
• The students in the class will confront this driving question, working in teams, with the teams cooperating, as they co-design a working system that can handle the two collections.
• There will be teams for ingesting content, indexing and searching (with ElasticSearch), clustering, topic analysis, and UX/interface development
• The instructor and several GRAs working on related research will provide guidance and assistance.
• This is one of the courses leading to a XCaliber Award "for making extraordinary contributions to technology enriched active learning".

About the Instructor

• Professor Edward A. Fox, fox@vt.edu, 540-231-5113, Torg. 2160G. Office hours are Tue/Thu 12:30-3, or by appointment.
• Dr. Fox is an ACM fellow as well as an IEEE Fellow: for contributions and leadership in information retrieval and digital libraries
• Dr. Fox's 1983 Ph.D. was supervised by Prof. Gerard Salton at Cornell University, often called "the father of information retrieval".
• GRA, working in 2030 Torg.: Ziqian Song, ziqian@vt.edu