Title
Extracting events from wikipedia as RDF triples linked to widespread semantic web datasets
Abstract
Many attempts have been made to extract structured data from Web resources, exposing them as RDF triples and interlinking them with other RDF datasets: in this way it is possible to create clouds of highly integrated Semantic Web data collections. In this paper we describe an approach to enhance the extraction of semantic contents from unstructured textual documents, in particular considering Wikipedia articles and focusing on event mining. Starting from the deep parsing of a set of English Wikipedia articles, we produce a semantic annotation compliant with the Knowledge Annotation Format (KAF). We extract events from the KAF semantic annotation and then we structure each event as a set of RDF triples linked to both DBpedia and WordNet. We point out examples of automatically mined events, providing some general evaluation of how our approach may discover new events and link them to existing contents.
Year
DOI
Venue
2011
10.1007/978-3-642-21796-8_10
HCI (18)
Keywords
Field
DocType
semantic web data collection,widespread semantic web datasets,rdf triple,english wikipedia article,rdf datasets,web resource,semantic annotation compliant,wikipedia article,event mining,semantic content,extracting event,kaf semantic annotation
Information retrieval,Semantic Web Stack,Computer science,Semantic Web,Linked data,Semantic analytics,SPARQL,Social Semantic Web,Semantic Web Rule Language,Semantic computing
Conference
Citations 
PageRank 
References 
1
0.39
9
Authors
5
Name
Order
Citations
PageRank
Carlo Aliprandi1344.82
Francesco Ronzano2355.03
Andrea Marchetti3509.53
Maurizio Tesconi428132.06
Salvatore Minutoli5298.58