H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 59 Citations 26,191 237 World Ranking 1673 National Ranking 66

Overview

What is he best known for?

The fields of study he is best known for:

  • Database
  • Operating system
  • Artificial intelligence

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

  • Semi-structured model that connect with fields like Document Schema Definition Languages and Data model,
  • XML schema and related Theoretical computer science. The study incorporates disciplines such as Data modeling, Database design, 3-dimensional matching, Blossom algorithm and Relational database in addition to Data warehouse. His Schema migration study incorporates themes from Star schema and Conceptual schema.

His most cited work include:

  • A survey of approaches to automatic schema matching (3112 citations)
  • Generic Schema Matching with Cupid (1307 citations)
  • Similarity flooding: a versatile graph matching algorithm and its application to schema matching (1264 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Information retrieval (23.33%)
  • Data mining (22.33%)
  • Data integration (14.33%)

What were the highlights of his more recent work (between 2017-2021)?

  • Scalability (12.00%)
  • Theoretical computer science (11.00%)
  • Record linkage (5.67%)

In recent papers he was focusing on the following fields of study:

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.

Between 2017 and 2021, his most popular works were:

  • Smart Medical Information Technology for Healthcare (SMITH). (31 citations)
  • Big Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities (25 citations)
  • Using Link Features for Entity Clustering in Knowledge Graphs (23 citations)

In his most recent research, the most cited papers focused on:

  • Database
  • Operating system
  • Artificial intelligence

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.

Top Publications

A survey of approaches to automatic schema matching

Erhard Rahm;Philip A. Bernstein.
very large data bases (2001)

4441 Citations

Data Cleaning: Problems and Current Approaches.

Erhard Rahm;Hong Hai Do.
IEEE Data(base) Engineering Bulletin (2000)

2417 Citations

Generic Schema Matching with Cupid

Jayant Madhavan;Philip A. Bernstein;Erhard Rahm.
very large data bases (2001)

2089 Citations

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)

2066 Citations

COMA: a system for flexible combination of schema matching approaches

Hong-Hai Do;Erhard Rahm.
very large data bases (2002)

1644 Citations

Schema and ontology matching with COMA

David Aumueller;Hong-Hai Do;Sabine Massmann;Erhard Rahm.
international conference on management of data (2005)

861 Citations

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)

642 Citations

Schema Matching and Mapping

Zohra Bellahsene;Angela Bonifati;Erhard Rahm.
smm (2013)

497 Citations

Frameworks for entity matching: A comparison

Hanna Köpcke;Erhard Rahm.
data and knowledge engineering (2010)

464 Citations

Rondo: a programming platform for generic model management

Sergey Melnik;Erhard Rahm;Philip A. Bernstein.
international conference on management of data (2003)

457 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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