The FP7 Multisensor project analyzes and extracts data from mass- and social media documents, including text, images and video, across several languages. It uses a number of ontologies for representing that data: NIF and OLIA for linguistic info, ITSRDF for NER, DBpedia and Babelnet for entities and concepts, MARL for sentiment, OA for image and cross-article annotations, etc. We'll present how all these ontologies fit together, and some innovations like embedding FrameNet in NIF.
%0 Generic
%1 Alexiev2016-dbpedia-multisensor
%A Alexiev, Vladimir
%B DBpedia Meeting
%C Leipzig, Germany
%D 2016
%K BabelNet CUBE FrameNet ITSRDF MARL Multisensor NERD NIF NLP NLP2RDF OLIA WordNet
%T Multisensor Linked Open Data
%X The FP7 Multisensor project analyzes and extracts data from mass- and social media documents, including text, images and video, across several languages. It uses a number of ontologies for representing that data: NIF and OLIA for linguistic info, ITSRDF for NER, DBpedia and Babelnet for entities and concepts, MARL for sentiment, OA for image and cross-article annotations, etc. We'll present how all these ontologies fit together, and some innovations like embedding FrameNet in NIF.
@misc{Alexiev2016-dbpedia-multisensor,
abstract = {The FP7 Multisensor project analyzes and extracts data from mass- and social media documents, including text, images and video, across several languages. It uses a number of ontologies for representing that data: NIF and OLIA for linguistic info, ITSRDF for NER, DBpedia and Babelnet for entities and concepts, MARL for sentiment, OA for image and cross-article annotations, etc. We'll present how all these ontologies fit together, and some innovations like embedding FrameNet in NIF.},
added-at = {2021-08-25T16:07:36.000+0200},
address = {Leipzig, Germany},
author = {Alexiev, Vladimir},
biburl = {https://www.bibsonomy.org/bibtex/2765dbc54686f0def6681f14455d4d9a1/valexiev},
booktitle = {DBpedia Meeting},
howpublished = {presentation},
interhash = {9e09cdd82589f0124dd976371698ede9},
intrahash = {765dbc54686f0def6681f14455d4d9a1},
keywords = {BabelNet CUBE FrameNet ITSRDF MARL Multisensor NERD NIF NLP NLP2RDF OLIA WordNet},
month = sep,
timestamp = {2021-08-25T16:07:36.000+0200},
title = {{Multisensor Linked Open Data}},
url_slides = {http://rawgit2.com/VladimirAlexiev/multisensor/master/20160915-Multisensor-LOD/index.html},
year = 2016
}