Navigating Multilingual News Collections Using Automatically Extracted Information
We are presenting a text analysis tool set that allows
analysts in various fields to sieve through large collections
of multilingual news items quickly and to find
information that is of relevance to them. For a given
document collection, the tool set automatically clusters
the texts into groups of similar articles, extracts names
of places, people and organisations, lists the user-defined
specialist terms found, links clusters and entities, and
generates hyperlinks. Through its daily news analysis
operating on thousands of articles per day, the tool also
learns relationships between people and other entities.
The fully functional prototype system allows users to
explore and navigate multilingual document collections
across languages and time.
STEINBERGER Ralf;
POULIQUEN Bruno;
IGNAT Camelia;
2006-11-16
University Computing Centre
JRC32639
https://publications.jrc.ec.europa.eu/repository/handle/JRC32639,
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