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Problem Based Learning To Build And Search Tweet And Web Archives

Learn about Problem-Based Learning to improve tweet and web archive search quality. Explore real-world disasters and events data provided by Virginia Tech. Discover courses and projects related to Computational Linguistics and Information Retrieval.

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Problem Based Learning To Build And Search Tweet And Web Archives

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  1. Problem Based Learning To Build And Search Tweet And Web Archives Richard Gruss Edward A. Fox Digital Library Research Laboratory Dept. of Computer Science Virginia Tech Blacksburg, VA, USA 21 May 2015 for Qatar National Library

  2. Integrated Digital Event Archiving and Library (IDEAL) www.eventsarchive.org https://archive-it.org/explore?q=virginia+tech&show=Collections

  3. IDEALprovided data for 2 courses: • Over 11 terabytes of webpages and about 1 billion tweets • Natural disasters (e.g., earthquakes, storms, floods) • Man-made disasters (e.g., protests, terrorism, conflicts) • Community / government events

  4. Problem-Based Learning (PBL) • A single question drives and organizes the learning activities. • Learning is done “Just-In-Time.” • Emphasis is placed on the process rather than the product. • The task of the instructor is to provide a relevant and authentic question and serve as a facilitator.

  5. CS 4984: Computational Linguistics, Fall 2014 • Undergraduate capstone course • Driving Question: “What is the best summary that can be automatically generated for your type of event?” • 7 teams, all performing the same analysis on different collections of text • Institutional Repository entries from the teams: http://vtechworks.lib.vt.edu/handle/10919/50956

  6. CS 4984: Computational Linguistics Text Collections

  7. CS 4984: Computational Linguistics Unit Objectives

  8. CS 4984: Computational Linguistics Sample Results

  9. CS 5604: Information Retrieval • Introductory graduate level course • Driving Question: “How can we best build a state-of-the-art IR system in support of a large digital library project?” • 8 teams, all performing different tasks along a processing pipeline • Institutional Repository entries from the teams: http://vtechworks.lib.vt.edu/handle/10919/19081

  10. CS 5604: Information Retrieval

  11. CS 5604: Information Retrieval Team Responsibilities

  12. CS 5604: Information Retrieval Indexing/analyzing Tweets into Solr

  13. CS 5604: Information Retrieval Custom Solr Search Field weights Custom result list processing

  14. CS 5604: Information Retrieval Search Performance (first 1000 results)

  15. Acknowledgements US National Science Foundation, DUE-1141209 US National Science Foundation, IIS-1319578

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