Two approaches to the dataset interlinking recommendation problem

Download statistics - Document (COUNTER):

Lopes, G.R.; Leme, L.A.P.P.; Pereira Nunes, B.; Casanova, M.A.; Dietze, S.: Two approaches to the dataset interlinking recommendation problem. In: Lecture Notes in Computer Science 8786 (2014), S. 324-339. DOI: https://doi.org/10.1007/978-3-319-11749-2_25

Repository version

To cite the version in the repository, please use this identifier: https://doi.org/10.15488/1380

Selected time period:

year: 
month: 

Sum total of downloads: 93




Thumbnail
Abstract: 
Whenever a dataset t is published on the Web of Data, an exploratory search over existing datasets must be performed to identify those datasets that are potential candidates to be interlinked with t. This paper introduces and compares two approaches to address the dataset interlinking recommendation problem, respectively based on Bayesian classifiers and on Social Network Analysis techniques. Both approaches define rank score functions that explore the vocabularies, classes and properties that the datasets use, in addition to the known dataset links. After extensive experiments using real-world datasets, the results show that the rank score functions achieve a mean average precision of around 60%. Intuitively, this means that the exploratory search for datasets to be interlinked with t might be limited to just the top-ranked datasets, reducing the cost of the dataset interlinking process. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-11749-2_25.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
Document Type: article
Publishing status: acceptedVersion
Issue Date: 2014
Appears in Collections:Fakultät für Elektrotechnik und Informatik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 63 67.74%
2 image of flag of France France 4 4.30%
3 image of flag of No geo information available No geo information available 3 3.23%
4 image of flag of United States United States 3 3.23%
5 image of flag of Russian Federation Russian Federation 3 3.23%
6 image of flag of United Kingdom United Kingdom 3 3.23%
7 image of flag of Liberia Liberia 2 2.15%
8 image of flag of India India 2 2.15%
9 image of flag of China China 2 2.15%
10 image of flag of Canada Canada 2 2.15%
    other countries 6 6.45%

Further download figures and rankings:


Hinweis

Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository


Browse