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What and Who
Title:Time for Text Mining and Information Retrieval
Speaker:Jannik Strötgen
coming from:Max-Planck-Institut für Informatik - D5
Speakers Bio:
Event Type:Joint Lecture Series
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Wednesday, 11 January 2017
Duration:60 Minutes
Building:E1 5
Temporal information is an important aspect in any information space and
has important characteristics that make it highly eligible to be
exploited in diverse text mining and information retrieval scenarios.
For quite a long time, only the metadata of text documents (e.g.,
publication dates) has been considered, but with recent improvements in
natural language processing (NLP), temporal expressions occurring in the
content of documents (e.g., "January 2016", "next week") can be
extracted and interpreted efficiently with high quality. This is
particularly valuable as in many types of documents, temporal
expressions do not only occur frequently but also play a crucial role,
e.g., to anchor events in time.

In this talk, after explaining the basics and challenges of the NLP task
"temporal tagging", I present our approach to enrich documents with
temporal information. Then, I showcase several application scenarios in
which we exploit automatically extracted temporal annotations for search
and exploration tasks. These range from temporal information retrieval
for news articles, via Wikipedia-based event extraction, up to the
exploration of fictitious happenings in literary texts in the context of
digital humanities research.
Name(s):Jennifer Müller
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:NoTo Location:
Tags, Category, Keywords and additional notes
Attachments, File(s):
Jennifer Müller/MPI-INF, 09/12/2016 03:47 PM
Last modified:
Uwe Brahm/MPII/DE, 01/11/2017 07:01 AM
  • Jennifer Müller, 09/12/2016 03:48 PM -- Created document.