loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Author: Fabien Duchateau

Affiliation: Université Lyon 1, France

ISBN: 978-989-8565-67-9

Keyword(s): Data Integration, Schema Matching, Ontology Alignment, Entity Resolution, Entity Matching, Selection of Correspondences.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Collaboration and e-Services ; Complex Systems Modeling and Simulation ; Data Engineering ; Data Management and Quality ; Data Structures and Data Management Algorithms ; e-Business ; Enterprise Information Systems ; Health Information Systems ; Information Integration ; Integration/Interoperability ; Interoperability ; Knowledge Engineering and Ontology Development ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Modeling and Managing Large Data Systems ; Ontologies and the Semantic Web ; Sensor Networks ; Simulation and Modeling ; Software Agents and Internet Computing ; Software and Architectures ; Symbolic Systems

Abstract: The Web 2.0 and the inexpensive cost of storage have pushed towards an exponential growth in the volume of collected and produced data. However, the integration of distributed and heterogeneous data sources has become the bottleneck for many applications, and it therefore still largely relies on manual tasks. One of this task, named matching or alignment, is the discovery of correspondences, i.e., semantically-equivalent elements in different data sources. Most approaches which attempt to solve this challenge face the issue of deciding whether a pair of elements is a correspondence or not, given the similarity value(s) computed for this pair. In this paper, we propose a generic and flexible framework for selecting the correspondences by relying on the discriminative similarity values for a pair. Running experiments on a public dataset has demonstrated the improvment in terms of quality and the robustness for adding new similarity measures without user intervention for tuning.

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.226.36.60

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Duchateau F. (2013). A Generic and Flexible Framework for Selecting Correspondences in Matching and Alignment Problems.In Proceedings of the 2nd International Conference on Data Technologies and Applications - Volume 1: DATA, ISBN 978-989-8565-67-9, pages 129-137. DOI: 10.5220/0004430401290137

@conference{data13,
author={Fabien Duchateau},
title={A Generic and Flexible Framework for Selecting Correspondences in Matching and Alignment Problems},
booktitle={Proceedings of the 2nd International Conference on Data Technologies and Applications - Volume 1: DATA,},
year={2013},
pages={129-137},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004430401290137},
isbn={978-989-8565-67-9},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Technologies and Applications - Volume 1: DATA,
TI - A Generic and Flexible Framework for Selecting Correspondences in Matching and Alignment Problems
SN - 978-989-8565-67-9
AU - Duchateau F.
PY - 2013
SP - 129
EP - 137
DO - 10.5220/0004430401290137

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.