CS6604 - Digital Libraries - Fall 2019

Why take CS6604?

• To allow you to work on your digital library related thesis or dissertation.
• To prepare you for research involving search engines, social media, natural language processing, text mining, classification, clustering, indexing, deep learning, Web archiving, and/or information seeking/exploration.
• To prepare you for teaching in Computer, Library, or Information Science departments/programs/schools related to any type of "information" courses or research.
• To prepare you for working at Google, Microsoft, or any company involved in searching, WWW, text, AI, and/or machine learning.
• To gain proficiency with parallel processing on clusters.
• To extend what you studied in CS5604 (Information Retrieval).

Resources

• Campus clusters with deep learning support like Cascades, Huckleberry and software like TensorFlow or PyTorch
• 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

• Free Books with Morgan and Claypool (through Library download), required:
  1. Theoretical Foundations for Digital Libraries (Fox/Goncalves/Shen)
  2. Key Issues Regarding Digital Libraries: Evaluation and Integration (Shen/Goncalves/Fox)
  3. Digital Library Technologies: Complex Objects, Annotation, Ontologies, Classification, Extraction, and Security (Fox/Torres, editors),
  4. Digital Library Applications: CBIR, Education, Social Networks, eScience/Simulation, and GIS (Fox/Leidig, editors)
  Supplemental website
• 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 CS6604 projects
• VTechWorks reports from CS5604 projects

Course Organization

• CS6604 Fall 2019 class: CRN 90122, TR, 11:00-12:15pm, McB 232
• Approach: seminar and team term project
• Goal: to help students progress toward their thesis or dissertation
• Seminar discussions: focused on key readings in the field selected by students based on relevance to their interests
• Term projects: in teams of 2-5, on topics identified by students
• See the page on the most recent (Spring 2017) prior version of this course. Note that this course in only rarely offered.

About the Instructor

• Professor Edward A. Fox, fox@vt.edu, 540-231-5113, Torg. 2160G. Office hours are TBD or by appointment.
• Dr. Fox's 1983 Ph.D. was supervised by Prof. Gerard Salton at Cornell University, often called "the father of information retrieval".
• He is a Fellow of ACM, and a Fellow of IEEE, cited for contributions to digital libraries and information retrieval, having helped found the digital library research field.
• He directs the Digital Library Research Laboratory (see there about its members, research, etc.), which can be utilized in this course.

Last updated 3/12/2019