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Machine reading for the Semantic Webold_uid | 13321 |
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title | Machine reading for the Semantic Web |
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start_date | 2014/01/24 |
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schedule | 11h-12h30 |
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online | no |
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location_info | salle 267 |
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summary | Machine reading is a mild version of natural language understanding,
aiming at extracting as many elements as possible from a text,
possibly on a large scale, and with performance appropriate to
industrial applications.
In recent years, machine reading in a pure NLP tradition has been
hybridised with semantic web techniques and standards, contributing
substantially to the productive area of “semantic technologies”.
In this seminar I make an overview of machine reading that applies, or
is used by, semantic web (in that area machine reading is better known
as “knowledge extraction from text”), and I will defend the position
that a closer collaboration and sharing of assumptions and objectives
can be mutually beneficial.
In order to show a concrete case study, I will detail one tool
designed by my group, FRED, which applies deep parsing and
computational semantics to generate well connected and linked RDF/OWL
graphs. |
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responsibles | Candito |
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