2023 - Research.com Computer Science in Germany Leader Award
His scientific interests lie mostly in Data mining, Schema matching, Information retrieval, Schema and Data warehouse. In general Data mining, his work in Information integration is often linked to Product linking many areas of study. His Schema matching study is concerned with the larger field of Data integration.
His research on Schema also deals with topics like
His primary areas of investigation include Information retrieval, Data mining, Data integration, Database and Ontology. The concepts of his Information retrieval study are interwoven with issues in Annotation, Set, World Wide Web and Domain. His work on Schema matching and Data warehouse as part of general Data mining study is frequently connected to Reuse, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Erhard Rahm works mostly in the field of Schema matching, limiting it down to topics relating to Schema migration and, in certain cases, Conceptual schema. His Data integration study combines topics in areas such as Linked data, Mashup and Information integration. His study focuses on the intersection of Database and fields such as Distributed computing with connections in the field of Online transaction processing, Cloud computing and Parallel computing.
His primary areas of study are Scalability, Theoretical computer science, Record linkage, Artificial intelligence and Data mining. The various areas that Erhard Rahm examines in his Scalability study include Domain, Cluster analysis, Linkage, Data science and Big data. His Theoretical computer science research includes elements of Graph, Graph, Power graph analysis, Dataflow and Visualization.
His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, Key, Pattern recognition and Natural language processing. His work in the fields of Data mining, such as Schema matching, intersects with other areas such as Scale. His Database research integrates issues from Hash function and Implementation.
Erhard Rahm mainly investigates Scalability, Data mining, Record linkage, Cluster analysis and Big data. His Scalability research is multidisciplinary, incorporating elements of Graph analytics, Graph database, Graph and Theoretical computer science. His studies deal with areas such as Visual analytics, Data management and Competence as well as Graph analytics.
Erhard Rahm regularly links together related areas like Data integration in his Cluster analysis studies. His Big data study frequently involves adjacent topics like Data science. His Privacy preserving research is multidisciplinary, relying on both Information sensitivity, Computer network and Dirty data.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A survey of approaches to automatic schema matching
Erhard Rahm;Philip A. Bernstein.
very large data bases (2001)
Data Cleaning: Problems and Current Approaches.
Erhard Rahm;Hong Hai Do.
IEEE Data(base) Engineering Bulletin (2000)
Similarity flooding: a versatile graph matching algorithm and its application to schema matching
S. Melnik;H. Garcia-Molina;E. Rahm.
international conference on data engineering (2002)
Generic Schema Matching with Cupid
Jayant Madhavan;Philip A. Bernstein;Erhard Rahm.
very large data bases (2001)
COMA: a system for flexible combination of schema matching approaches
Hong-Hai Do;Erhard Rahm.
very large data bases (2002)
Schema and ontology matching with COMA
David Aumueller;Hong-Hai Do;Sabine Massmann;Erhard Rahm.
international conference on management of data (2005)
Comparison of Schema Matching Evaluations
Hong Hai Do;Sergey Melnik;Erhard Rahm.
Revised Papers from the NODe 2002 Web and Database-Related Workshops on Web, Web-Services, and Database Systems (2002)
Schema Matching and Mapping
Zohra Bellahsene;Angela Bonifati;Erhard Rahm.
Frameworks for entity matching: A comparison
Hanna Köpcke;Erhard Rahm.
data and knowledge engineering (2010)
Evaluation of entity resolution approaches on real-world match problems
Hanna Köpcke;Andreas Thor;Erhard Rahm.
very large data bases (2010)
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