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 userdefined
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 relationshipsbetween 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;
2006-10-03
SRCE University Computing Centre, University of Zagreb
JRC31102
https://publications.jrc.ec.europa.eu/repository/handle/JRC31102,
10.1016/j.dsr2.2006.01.027,
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