Towards Joint Inference for Complex Ontology Matching


Meilicke, Christian ; Noessner, Jan ; Stuckenschmidt, Heiner



URL: http://www.aaai.org/ocs/index.php/WS/AAAIW13/paper...
Additional URL: http://www.aaai.org/Library/Workshops/ws13-17.php
Document Type: Conference or workshop publication
Year of publication: 2013
Book title: Late-Breaking Developments in the Field of Artificial Intelligence : Papers Presented at the Twenty-Seventh AAAI Conference on Artificial Intelligence
The title of a journal, publication series: Technical report / Association for the Advancement of Artificial Intelligence. WS
Volume: 13-17
Page range: 80-82
Location of the conference venue: Bellevue, Wash.
Date of the conference: July 16, 2013
Place of publication: Palo Alto, Calif.
Publishing house: AAAI Press
ISBN: 978-1-57735-628-8
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: In this paper, we show how to model the matching problem as a problem of joint inference. In opposite to existing approaches, we distinguish between the layer of labels and the layer of concepts and properties. Entities from both layers appear as first class citizens in our model. We present an ex-ample and explain the benefits of our approach. Moreover, we argue that our approach can be extended to generate correspondences involving complex concept descriptions.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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