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Original scientific paper
https://doi.org/10.2498/cit.2005.04.01

Navigating Multilingual News Collections Using Automatically Extracted Information

Camelia Ignat
Ralf Steinberger
Bruno Pouliquen

Fulltext: english, pdf (1 MB) pages 257-264 downloads: 630* cite
APA 6th Edition
Ignat, C., Steinberger, R. & Pouliquen, B. (2005). Navigating Multilingual News Collections Using Automatically Extracted Information. Journal of computing and information technology, 13 (4), 257-264. https://doi.org/10.2498/cit.2005.04.01
MLA 8th Edition
Ignat, Camelia, et al. "Navigating Multilingual News Collections Using Automatically Extracted Information." Journal of computing and information technology, vol. 13, no. 4, 2005, pp. 257-264. https://doi.org/10.2498/cit.2005.04.01. Accessed 5 Jul. 2020.
Chicago 17th Edition
Ignat, Camelia, Ralf Steinberger and Bruno Pouliquen. "Navigating Multilingual News Collections Using Automatically Extracted Information." Journal of computing and information technology 13, no. 4 (2005): 257-264. https://doi.org/10.2498/cit.2005.04.01
Harvard
Ignat, C., Steinberger, R., and Pouliquen, B. (2005). 'Navigating Multilingual News Collections Using Automatically Extracted Information', Journal of computing and information technology, 13(4), pp. 257-264. https://doi.org/10.2498/cit.2005.04.01
Vancouver
Ignat C, Steinberger R, Pouliquen B. Navigating Multilingual News Collections Using Automatically Extracted Information. Journal of computing and information technology [Internet]. 2005 [cited 2020 July 05];13(4):257-264. https://doi.org/10.2498/cit.2005.04.01
IEEE
C. Ignat, R. Steinberger and B. Pouliquen, "Navigating Multilingual News Collections Using Automatically Extracted Information", Journal of computing and information technology, vol.13, no. 4, pp. 257-264, 2005. [Online]. https://doi.org/10.2498/cit.2005.04.01

Abstracts
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.

Hrčak ID: 44675

URI
https://hrcak.srce.hr/44675

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