H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 40 Citations 16,340 115 World Ranking 4623 National Ranking 211

Overview

What is he best known for?

The fields of study he is best known for:

  • Database
  • Artificial intelligence
  • Programming language

Bernhard Seeger mainly focuses on Theoretical computer science, Joins, Algorithm, Data set and Data mining. Bernhard Seeger interconnects Testbed, M-tree and External storage in the investigation of issues within Theoretical computer science. His studies deal with areas such as Tree, Range query and Heuristic as well as M-tree.

His iDistance research extends to Algorithm, which is thematically connected. His work deals with themes such as Asymptotically optimal algorithm, Spatial database and B-tree, which intersect with Data set. His research in the fields of Skyline, Nearest neighbor search and Skyline computation overlaps with other disciplines such as Simple.

His most cited work include:

  • The R*-tree: an efficient and robust access method for points and rectangles (3895 citations)
  • Progressive skyline computation in database systems (756 citations)
  • An optimal and progressive algorithm for skyline queries (727 citations)

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

His primary areas of study are Data mining, Theoretical computer science, Algorithm, Distributed computing and Data stream mining. His Data mining research is multidisciplinary, incorporating perspectives in Search engine indexing and Statistical model. Bernhard Seeger usually deals with Theoretical computer science and limits it to topics linked to Spatial analysis and Visualization.

His Algorithm research integrates issues from Set, Joins and R-tree. His research in Distributed computing intersects with topics in Event, Complex event processing and Real-time computing. Bernhard Seeger interconnects Query optimization and Data analysis in the investigation of issues within Data stream mining.

He most often published in these fields:

  • Data mining (27.46%)
  • Theoretical computer science (19.01%)
  • Algorithm (14.08%)

What were the highlights of his more recent work (between 2016-2020)?

  • Herbarium (4.23%)
  • Complex event processing (8.45%)
  • Artificial intelligence (6.34%)

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

Bernhard Seeger spends much of his time researching Herbarium, Complex event processing, Artificial intelligence, Convolutional neural network and Data science. His Complex event processing research incorporates elements of User space, Software, Latency and Data mining. His study looks at the relationship between Latency and fields such as Timestamp, as well as how they intersect with chemical problems.

His studies link Latency with Algorithm. His work on Analytics as part of general Data mining research is often related to Distribution, thus linking different fields of science. His studies deal with areas such as Workflow and Pattern recognition as well as Artificial intelligence.

Between 2016 and 2020, his most popular works were:

  • Fast Cloud Segmentation Using Convolutional Neural Networks (33 citations)
  • Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks (26 citations)
  • ChronicleDB: A High-Performance Event Store. (9 citations)

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

  • Database
  • Artificial intelligence
  • Programming language

His primary areas of investigation include Real-time computing, Event, Convolutional neural network, Latency and Pattern matching. His Real-time computing study which covers Leverage that intersects with Complex event processing. He has included themes like Kernel and Sensor hub in his Complex event processing study.

His Convolutional neural network research is multidisciplinary, incorporating perspectives in Segmentation and Trait. The Latency study combines topics in areas such as Timestamp, Event, Feature and Latency. As part of his studies on Event, Bernhard Seeger frequently links adjacent subjects like Algorithm.

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

The R*-tree: an efficient and robust access method for points and rectangles

Norbert Beckmann;Hans-Peter Kriegel;Ralf Schneider;Bernhard Seeger.
international conference on management of data (1990)

6422 Citations

Progressive skyline computation in database systems

Dimitris Papadias;Yufei Tao;Greg Fu;Bernhard Seeger.
international conference on management of data (2005)

1047 Citations

An optimal and progressive algorithm for skyline queries

Dimitris Papadias;Yufei Tao;Greg Fu;Bernhard Seeger.
international conference on management of data (2003)

1023 Citations

Efficient processing of spatial joins using R-trees

Thomas Brinkhoff;Hans-Peter Kriegel;Bernhard Seeger.
international conference on management of data (1993)

959 Citations

An asymptotically optimal multiversion B-tree

Bruno Becker;Stephan Gschwind;Thomas Ohler;Bernhard Seeger.
very large data bases (1996)

487 Citations

Slim-Trees: High Performance Metric Trees Minimizing Overlap Between Nodes

Caetano Traina;Agma J. M. Traina;Bernhard Seeger;Christos Faloutsos.
extending database technology (2000)

393 Citations

Multi-step processing of spatial joins

Thomas Brinkhoff;Hans-Peter Kriegel;Ralf Schneider;Bernhard Seeger.
international conference on management of data (1994)

382 Citations

Efficient computation of reverse skyline queries

Evangelos Dellis;Bernhard Seeger.
very large data bases (2007)

359 Citations

The Buddy-Tree: An Efficient and Robust Access Method for Spatial Data Base Systems

Bernhard Seeger;Hans-Peter Kriegel.
very large data bases (1990)

271 Citations

Fast indexing and visualization of metric data sets using slim-trees

C. Traina;A. Traina;C. Faloutsos;B. Seeger.
IEEE Transactions on Knowledge and Data Engineering (2002)

270 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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Top Scientists Citing Bernhard Seeger

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