TY - GEN
T1 - T2R
T2 - 2013 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IATW 2013
AU - Hassanzadeh, Kimia
AU - Reformat, Marek
AU - Pedrycz, Witold
AU - Jamal, Iqbal
AU - Berezowski, John
PY - 2013
Y1 - 2013
N2 - An important contribution of the Semantic Web is a new format of data representation called Resource Description Framework (RDF). In RDF, every piece of information is represented as a triple: subject-property-object. In general, subjects and objects can be shared between multiple RDF triples, and all triples can constitute a densely interlinked network. RDF becomes a very popular format of representing data on the web. As of September 2012, the last available data, more than 31 billions of triples exist on the web. In the paper, we propose a system - called T2R - for automatic acquisition of syntactic and semantic relations among terms from a plain text. These relations are expressed in the form of RDF triples. The proposed method is independent of any prior knowledge and domain specific patterns, and is applicable to any textual resources. The system implementing the approach is capable of identifying grammatical structure of an input sentence and analysing its semantics to generate meaningful RDF triples. We evaluate this approach by proving the quality of our results through case studies.
AB - An important contribution of the Semantic Web is a new format of data representation called Resource Description Framework (RDF). In RDF, every piece of information is represented as a triple: subject-property-object. In general, subjects and objects can be shared between multiple RDF triples, and all triples can constitute a densely interlinked network. RDF becomes a very popular format of representing data on the web. As of September 2012, the last available data, more than 31 billions of triples exist on the web. In the paper, we propose a system - called T2R - for automatic acquisition of syntactic and semantic relations among terms from a plain text. These relations are expressed in the form of RDF triples. The proposed method is independent of any prior knowledge and domain specific patterns, and is applicable to any textual resources. The system implementing the approach is capable of identifying grammatical structure of an input sentence and analysing its semantics to generate meaningful RDF triples. We evaluate this approach by proving the quality of our results through case studies.
UR - http://www.scopus.com/inward/record.url?scp=84893225770&partnerID=8YFLogxK
U2 - 10.1109/WI-IAT.2013.187
DO - 10.1109/WI-IAT.2013.187
M3 - Conference contribution
AN - SCOPUS:84893225770
SN - 9781479929023
T3 - Proceedings - 2013 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IATW 2013
SP - 221
EP - 228
BT - Proceedings - 2013 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IATW 2013
Y2 - 17 November 2013 through 20 November 2013
ER -