H-Index & Metrics Top Publications
Wolfgang Lehner

Wolfgang Lehner

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 40 Citations 7,051 381 World Ranking 4590 National Ranking 209

Research.com Recognitions

Awards & Achievements

2014 - Member of Academia Europaea

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Database
  • Programming language

Wolfgang Lehner mostly deals with Data mining, Database, Data warehouse, Query optimization and Online analytical processing. His Data mining research is multidisciplinary, relying on both Data modeling, Data stream and Sample. His research integrates issues of Exploit and Data structure in his study of Database.

His Data warehouse study combines topics from a wide range of disciplines, such as Java and Architecture framework. The various areas that Wolfgang Lehner examines in his Query optimization study include Sample size determination, Sampling, Reservoir sampling, Web query classification and Sargable. Wolfgang Lehner combines subjects such as Curse of dimensionality and Data science with his study of Online analytical processing.

His most cited work include:

  • SAP HANA database: data management for modern business applications (352 citations)
  • The SAP HANA Database - An Architecture Overview (208 citations)
  • Modelling Large Scale OLAP Scenarios (165 citations)

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

His scientific interests lie mostly in Data mining, Database, Distributed computing, Theoretical computer science and Data warehouse. His study in Data mining focuses on Online analytical processing in particular. His work in Database is not limited to one particular discipline; it also encompasses Software engineering.

His studies in Theoretical computer science integrate themes in fields like Graph database, Graph and Query optimization. His Graph database study results in a more complete grasp of Graph.

He most often published in these fields:

  • Data mining (21.28%)
  • Database (19.73%)
  • Distributed computing (10.83%)

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

  • Parallel computing (8.90%)
  • Distributed computing (10.83%)
  • Data compression (4.45%)

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

The scientist’s investigation covers issues in Parallel computing, Distributed computing, Data compression, Big data and Artificial intelligence. His Distributed computing research is multidisciplinary, incorporating elements of Multi-core processor, Overhead and Set. His Data compression course of study focuses on Speedup and Field and Instruction set.

Wolfgang Lehner interconnects Partition, Selection and Data science in the investigation of issues within Big data. The Artificial intelligence study combines topics in areas such as Machine learning and Natural language processing. His work in Memory footprint addresses issues such as Data mining, which are connected to fields such as Time series.

Between 2017 and 2021, his most popular works were:

  • Cardinality estimation with local deep learning models (28 citations)
  • Big Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities (25 citations)
  • Table Recognition in Spreadsheets via a Graph Representation (16 citations)

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

  • Operating system
  • Database
  • Artificial intelligence

His primary areas of investigation include Data compression, Speedup, Distributed computing, Vectorization and Overhead. His Distributed computing research incorporates themes from Energy control, In-memory database, Multi-core processor and Hardware compatibility list. His Overhead study integrates concerns from other disciplines, such as SAP HANA, Analytics, Shared resource and Data structure.

His research in Data structure focuses on subjects like Big data, which are connected to Data management. His Data management study combines topics in areas such as Cardinality and Machine learning. His SIMD research includes elements of Entity–relationship model, Database design, Relational database, View and Database model.

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

SAP HANA database: data management for modern business applications

Franz Färber;Sang Kyun Cha;Jürgen Primsch;Christof Bornhövd.
international conference on management of data (2012)

512 Citations

The SAP HANA Database - An Architecture Overview

Franz Färber;Norman May;Wolfgang Lehner;Philipp Große.
IEEE Data(base) Engineering Bulletin (2012)

328 Citations

Modelling Large Scale OLAP Scenarios

Wolfgang Lehner.
extending database technology (1998)

270 Citations

Efficient transaction processing in SAP HANA database: the end of a column store myth

Vishal Sikka;Franz Färber;Wolfgang Lehner;Sang Kyun Cha.
international conference on management of data (2012)

233 Citations

Normal forms for multidimensional databases

W. Lehner;J. Albrecht;H. Wedekind.
statistical and scientific database management (1998)

206 Citations

FPTree: A Hybrid SCM-DRAM Persistent and Concurrent B-Tree for Storage Class Memory

Ismail Oukid;Johan Lasperas;Anisoara Nica;Thomas Willhalm.
international conference on management of data (2016)

199 Citations

Euro-Par 2006 Parallel Processing

Wolfgang Lehner;Norbert Meyer;Achim Streit;Craig Stewart.
(2006)

187 Citations

Efficient exploitation of similar subexpressions for query processing

Jingren Zhou;Per-Ake Larson;Johann-Christoph Freytag;Wolfgang Lehner.
international conference on management of data (2007)

132 Citations

Representing Data Quality in Sensor Data Streaming Environments

A. Klein;W. Lehner.
Journal of Data and Information Quality (2009)

123 Citations

RiTE: Providing On-Demand Data for Right-Time Data Warehousing

C. Thomsen;T.B. Pedersen;W. Lehner.
international conference on data engineering (2008)

84 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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