NDLI: Automatic Mapping of Wikipedia Templates for Fast Deployment of Localised DBpedia Datasets

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Automatic Mapping of Wikipedia Templates for Fast Deployment of Localised DBpedia Datasets

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Automatic Mapping of Wikipedia Templates for Fast Deployment of Localised DBpedia Datasets

Content Provider	ACM Digital Library
Author	Giuliano, Claudio Lavelli, Alberto Aprosio, Alessio Palmero
Abstract	DBpedia is a Semantic Web resource that aims at representing Wikipedia in RDF triples. Due to the large and growing number of resources linked to it, DBpedia has become central for the Semantic Web community. The English version currently covers around 1.7M Wikipedia pages. However, the English Wikipedia contains almost 4M pages. This means that there is a substantial problem of coverage (even bigger in other languages). The coverage slowly increases thanks to the manual effort made by various local communities. This effort is aimed at manually mapping Wikipedia templates into DBpedia ontology classes and then run the open-source software provided by the DBpedia community to extract the triples. In this paper, we present an approach to automatically map templates and we release the resulting resource in 25 languages. We describe the used algorithm, starting from the existing mappings on other languages and extending them using the cross-lingual information available in Wikipedia. We evaluate our system on the mappings of a set of languages already included in DBpedia (but not used during the training phase), demonstrating that our approach can replicate the human mappings with high precision and recall, and producing an additional set of mappings not included in the original DBpedia.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450323000
DOI	10.1145/2494188.2494196
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-09-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Ontology population Semantic web Dbpedia Linked open data
Content Type	Text
Resource Type	Article

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