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Erhard Rahm
Researcher at Leipzig University
Publications - 331
Citations - 21198
Erhard Rahm is an academic researcher from Leipzig University. The author has contributed to research in topics: Data integration & Ontology (information science). The author has an hindex of 54, co-authored 314 publications receiving 20263 citations. Previous affiliations of Erhard Rahm include University of Duisburg-Essen & Microsoft.
Papers
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Journal ArticleDOI
A survey of approaches to automatic schema matching
Erhard Rahm,Philip A. Bernstein +1 more
TL;DR: A taxonomy is presented that distinguishes between schema-level and instance-level, element- level and structure- level, and language-based and constraint-based matchers and is intended to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component.
Journal Article
Data Cleaning: Problems and Current Approaches.
Erhard Rahm,Hong Hai Do +1 more
TL;DR: This work classifies data quality problems that are addressed by data cleaning and provides an overview of the main solution approaches and discusses current tool support for data cleaning.
Proceedings ArticleDOI
Similarity flooding: a versatile graph matching algorithm and its application to schema matching
TL;DR: This paper presents a matching algorithm based on a fixpoint computation that is usable across different scenarios and conducts a user study, in which the accuracy metric was used to estimate the labor savings that the users could obtain by utilizing the algorithm to obtain an initial matching.
Proceedings Article
Generic Schema Matching with Cupid
TL;DR: This paper proposes a new algorithm, Cupid, that discovers mappings between schema elements based on their names, data types, constraints, and schema structure, using a broader set of techniques than past approaches.
Book ChapterDOI
COMA: a system for flexible combination of schema matching approaches
Hong-Hai Do,Erhard Rahm +1 more
TL;DR: This work develops the COMA schema matching system as a platform to combine multiple matchers in a flexible way and uses COMA as a framework to comprehensively evaluate the effectiveness of different matchers and their combinations for real-world schemas.