Probabilistic-Logical Web Data Integration


Niepert, Mathias ; Noessner, Jan ; Meilicke, Christian ; Stuckenschmidt, Heiner



DOI: https://doi.org/10.1007/978-3-642-23032-5_11
URL: https://link.springer.com/chapter/10.1007%2F978-3-...
Document Type: Conference or workshop publication
Year of publication: 2011
Book title: Reasoning Web. Semantic Technologies for the Web of Data : 7th International Summer School 2011, Galway, Ireland, August 23-27, 2011, Tutorial Lectures
The title of a journal, publication series: Lecture Notes in Computer Science
Volume: 6848
Page range: 504-533
Conference title: 7th Reasoning Web International Summer School 2011
Location of the conference venue: Galway, Ireland
Date of the conference: August 23-27, 2011
Author/Publisher of the book
(only the first ones mentioned)
:
Polleres, Axel
Place of publication: Berlin [u.a.]
Publishing house: Springer
ISBN: 978-3-642-23031-8 , 978-3-642-23032-5
Publication language: English
Institution: Außerfakultäre Einrichtungen > Institut für Enterprise Systems (InES)
School of Business Informatics and Mathematics > Praktische Informatik II (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: The integration of both distributed schemas and data repositories is a major challenge in data and knowledge management applications. Instances of this problem range from mapping database schemas to object reconciliation in the linked open data cloud. We present a novel approach to several important data integration problems that combines logical and probabilistic reasoning. We first provide a brief overview of some of the basic formalisms such as description logics and Markov logic that are used in the framework. We then describe the representation of the different integration problems in the probabilistic-logical framework and discuss efficient inference algorithms. For each of the applications, we conducted extensive experiments on standard data integration and matching benchmarks to evaluate the efficiency and performance of the approach. The positive results of the evaluation are quite promising and the flexibility of the framework makes it easily adaptable to other real-world data integration problems.

Dieser Eintrag ist Teil der Universitätsbibliographie.




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Niepert, Mathias ; Noessner, Jan ; Meilicke, Christian ; Stuckenschmidt, Heiner ORCID: 0000-0002-0209-3859 Probabilistic-Logical Web Data Integration. Polleres, Axel Lecture Notes in Computer Science 6848 504-533 In: Reasoning Web. Semantic Technologies for the Web of Data : 7th International Summer School 2011, Galway, Ireland, August 23-27, 2011, Tutorial Lectures (2011) Berlin [u.a.] 7th Reasoning Web International Summer School 2011 (Galway, Ireland) [Conference or workshop publication]


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