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Erschienen in:
Automatic Key Selection for Data Linking Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

TAIPAN: Automatic Property Mapping for Tabular Data

verfasst von : Ivan Ermilov, Axel-Cyrille Ngonga Ngomo

Erschienen in: Knowledge Engineering and Knowledge Management

Verlag: Springer International Publishing

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Abstract

The Web encompasses a significant amount of knowledge hidden in entity-attributes tables. Bridging the gap between these tables and the Web of Data thus has the potential to facilitate a large number of applications, including the augmentation of knowledge bases from tables, the search for related tables and the completion of tables using knowledge bases. Computing such bridges is impeded by the poor accuracy of automatic property mapping, the lack of approaches for the discovery of subject columns and the mere size of table corpora. We propose Taipan, a novel approach for recovering the semantics of tables. Our approach begins by identifying subject columns using a combination of structural and semantic features. It then maps binary relations inside a table to predicates from a given knowledge base. Therewith, our solution supports both the tasks of table expansion and knowledge base augmentation. We evaluate our approach on a table dataset generated from real RDF data and a manually curated version of the T2D gold standard. Our results suggest that we outperform the state of the art by up to 85 % F-measure.

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Vorheriges Kapitel A Query Model to Capture Event Pattern Matching in RDF Stream Processing Query Languages
Nächstes Kapitel Semantic Authoring of Ontologies by Exploration and Elimination of Possible Worlds
Fußnoten
10
Accuracy is defined as a ratio of correctly guessed subject columns to a number of overall guessed subject columns.
 
11
We contacted the authors to obtain their corpus but were not provided access to it. Still, we followed the specification of the SVM in their paper exactly.
 
12
We used the classifier implementations from scikit-learn python library at http://​scikit-learn.​org/​. For more information on the implementation, please refer to the Taipan Github repository at https://​github.​com/​AKSW/​TAIPAN.
 
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Metadaten
Titel
TAIPAN: Automatic Property Mapping for Tabular Data
verfasst von
Ivan Ermilov
Axel-Cyrille Ngonga Ngomo
Copyright-Jahr
2016
Buch
Knowledge Engineering and Knowledge Management

Print ISBN: 978-3-319-49003-8

Electronic ISBN: 978-3-319-49004-5

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-49004-5_11