Automatic Discovery of High-Level Provenance Using Semantic Similarity-Reference-Cited by-同舟云学术

Automatic Discovery of High-Level Provenance Using Semantic Similarity

Published:2012 Issue: Volume: Page:97-110
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

De Nies Tom,Coppens Sam,Van Deursen Davy,Mannens Erik,Van de Walle Rik

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-34222-6_8

Reference13 articles.

1. Gil, Y., Cheney, J., Groth, P., Hartig, O., Miles, S., Moreau, L., Da Silva, P.P.: Provenance XG final report. Final Incubator Group Report (2010)

2. Gómez-Pérez, J.M., Corcho, O.: Problem-solving methods for understanding process executions. IEEE Computing in Science & Engineering 10, 47–52 (2008)

3. Lecture Notes in Computer Science;U. Braun,2006

4. PROV-DM Part 1: The Provenance Data Model, W3C Editor’s Draft (May 29, 2012), http://dvcs.w3.org/hg/prov/raw-file/default/model/prov-dm.html

5. Rizzo, G., Troncy, R.: NERD: Evaluating Named Entity Recognition Tools in the Web of Data. In: Workshop on Web Scale Knowledge Extraction, WEKEX 2011 (2011)

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