Natural Language Processing and the Web

Natural Language Processing and the Web

Teaching Staff

  • Prof. Dr. Iryna Gurevych
  • Dr. Thomas Arnold
  • Naveen Kumar

We currently do not have fixed office hours, so please contact us by mail to get an appointment.

Organization

  • Lecture: Tuesday 09:50-11:30, Room S202 / C120 starting October 16
  • Practice class: Thursday 16:15-17:55, Room S202/C120 starting October 25

The learning material is available from the Moodle eLeaning platform.

Registration

If you plan to participate in this course, please register on Tucan.

Requirements

To pass, each student has to take the written exam at the end of the semester.

There will also be a project in the practice class which will contribute to your overall grade.

Exam

  • Date/Time: Not fixed yet
  • Room: S202/C205 – Bosch Hörsaal

Course content

The Web contains more than 10 billion indexable web pages, which can be retrieved via search queries. The lecture will present Natural Language Processing (NLP) methods to (1) automatically process large amounts of unstructured text from the web and (2) analyse the use of Web data as a resource for other NLP tasks.

Processing of unstructured web content

  • Introduction
  • NLP Basics – Tokenisation, Part of Speech Tagging, Chunking, Stemming, Lemmatization
  • Web contents and their characteristics – diverse genres of web contents, e.g. personal web sites, news sites, blogs, forums, wikis
  • Web contents and their characteristics – continued

NLP applications for the web

  • Information retrieval – introduction to the basics of information retrieval
  • Web information retrieval – natural language interfaces for web information retrieval
  • Question answering (QA): Factoid QA, Knowledge Base QA, Community QA
  • Crowdsourcing
  • Text Structuring

Literature

  • Kai-Uwe Carstensen, Christian Ebert, Cornelia Endriss, Susanne Jekat, Ralf Klabunde, Computerlinguistik und Sprachtechnologie. Eine Einführung, Heidelberg: Spektrum-Verlag, März 2010. (3. Auflage) I
  • T. Götz & O. Suhre, Design and implementation of the UIMA Common Analysis System, IBM Systems Journal, 2004, 43, 476-489.
  • Adam Kilgarriff & Gregory Grefenstette, Introduction to the special issue on the web as corpus, Computational Linguistics, MIT Press, 2003, 29, 333-347
  • Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.