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Abstract :
Benoît Sagot, head of the ALMAnaCH project team, presents the work of his team in 180 seconds.
Textual documents are varied (they can be old or new, legal or not, produced by institutions or individuals) and therefore cause problems when processed by computers. From these texts, people may want to extract information, correct them, simplify them, translate them, classify them, perform statistical analysis - whatever the volume or the state of the original documents.
ALMAnaCH has developed tools based on machine learning to meet these needs: morpho-syntactic labels, syntactic or semantic analysis.
It also helps to better understand how languages work, and what are their evolutions, and to develop new approaches in humanities and social sciences (aka digital humanities).
Date of production :
Duration (mn) :
00:03:26
Language :
Version française
Available languages :
Français
Research project-team :
Research center :
Keywords :
Master N° :
1190
Scientific author :
Production :
Inria - Direction de la communication
Author director :
Langlois, Arnaud
Permalink :
Inria-1190-ALMANACH-180s_VF.mp4

Format : .mp4
384,4 MB
1920 x 1080 pixels
Inria-1190-ALMANACH-180s_BDWeb.MP4

Format : .mp4
15,8 MB
480 x 270 pixels
Basse défiinition - Web
Encodage PAL .MP4 H264
512 kbits/s
Encodage PAL .MP4 H264
512 kbits/s
Inria-1190-ALMANACH-180s_HD.MP4

Format : .mp4
125,8 MB
1024 x 576 pixels
Moyenne définition - équivalent DVD
Encodage PAL .MP4 H264
5 Mbits/s
Encodage PAL .MP4 H264
5 Mbits/s
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