Torsten Grabs

551 total citations
18 papers, 215 citations indexed

About

Torsten Grabs is a scholar working on Computer Networks and Communications, Signal Processing and Information Systems. According to data from OpenAlex, Torsten Grabs has authored 18 papers receiving a total of 215 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Networks and Communications, 6 papers in Signal Processing and 4 papers in Information Systems. Recurrent topics in Torsten Grabs's work include Advanced Database Systems and Queries (16 papers), Distributed systems and fault tolerance (9 papers) and Data Management and Algorithms (6 papers). Torsten Grabs is often cited by papers focused on Advanced Database Systems and Queries (16 papers), Distributed systems and fault tolerance (9 papers) and Data Management and Algorithms (6 papers). Torsten Grabs collaborates with scholars based in United States, Switzerland and Germany. Torsten Grabs's co-authors include Hans‐Jörg Schek, Klemens Böhm, César Galindo-Legaria, Gerhard Weikum, Henk Blanken, Ralf Schenkel, Yuri Breitbart, Can Türker, Lourens Veen and Fuat Akal and has published in prestigious journals such as Knowledge and Information Systems, Very Large Data Bases and Repository for Publications and Research Data (ETH Zurich).

In The Last Decade

Torsten Grabs

16 papers receiving 184 citations

Peers

Torsten Grabs
Mohamed Ziauddin United States
Khaled Yagoub United States
Richard Tibbetts United States
Kai Großjohann Germany
Leonidas Galanis United States
Gilles Zurfluh France
Michael S. Kester United States
Kazimierz Subieta Poland
Michael Minock Sweden
Ralph Busse Netherlands
Mohamed Ziauddin United States
Torsten Grabs
Citations per year, relative to Torsten Grabs Torsten Grabs (= 1×) peers Mohamed Ziauddin

Countries citing papers authored by Torsten Grabs

Since Specialization
Citations

This map shows the geographic impact of Torsten Grabs's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Torsten Grabs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Torsten Grabs more than expected).

Fields of papers citing papers by Torsten Grabs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Torsten Grabs. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Torsten Grabs. The network helps show where Torsten Grabs may publish in the future.

Co-authorship network of co-authors of Torsten Grabs

This figure shows the co-authorship network connecting the top 25 collaborators of Torsten Grabs. A scholar is included among the top collaborators of Torsten Grabs based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Torsten Grabs. Torsten Grabs is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Galindo-Legaria, César, et al.. (2008). Optimizing Star Join Queries for Data Warehousing in Microsoft SQL Server. 1190–1199. 15 indexed citations
2.
Grabs, Torsten, et al.. (2008). Testing challenges for extending SQL server's query processor. 1–6. 2 indexed citations
3.
Galindo-Legaria, César, et al.. (2007). Optimizing Similar Scalar Subqueries for XML Processing in Microsoft SQL Server. dbpl 1993. 1164–1173. 2 indexed citations
4.
Galindo-Legaria, César, et al.. (2007). Execution strategies for SQL subqueries. 993–1004. 40 indexed citations
5.
Akal, Fuat, Can Türker, Hans‐Jörg Schek, et al.. (2005). Fine-grained replication and scheduling with freshness and correctness guarantees. Very Large Data Bases. 565–576. 22 indexed citations
6.
Galindo-Legaria, César, et al.. (2005). Database change notifications: primitives for efficient database query result caching. Very Large Data Bases. 1275–1278. 5 indexed citations
7.
Grabs, Torsten, Klemens Böhm, & Hans‐Jörg Schek. (2004). PowerDB-IR – Scalable Information Retrieval and Storage with a Cluster of Databases. Knowledge and Information Systems. 6(4). 465–505. 8 indexed citations
8.
Blanken, Henk, Torsten Grabs, Hans‐Jörg Schek, Ralf Schenkel, & Gerhard Weikum. (2003). Intelligent Search on XML Data: Applications, Languages, Models, Implementations, and Benchmarks. DIAL (Catholic University of Leuven). 23 indexed citations
9.
Grabs, Torsten. (2003). Storage and Retrieval of XML Documents with a Cluster of Database Systems. CERN Document Server (European Organization for Nuclear Research).
10.
Grabs, Torsten, et al.. (2002). Scalable distributed query and update service implementations for XML document elements. 2000. 35–42. 5 indexed citations
11.
Grabs, Torsten & Hans‐Jörg Schek. (2002). ETH Zürich at INEX: Flexible Information Retrieval from XML with PowerDB-XML.. 141–148. 12 indexed citations
12.
Grabs, Torsten, Klemens Böhm, & Hans‐Jörg Schek. (2002). XMLTM. 2 indexed citations
13.
Grabs, Torsten, Klemens Böhm, & Hans‐Jörg Schek. (2002). XMLTM. 142–152. 24 indexed citations
14.
Grabs, Torsten, et al.. (2002). High-level parallelisation in a database cluster: a feasibility study using document services. 121–130. 6 indexed citations
15.
Grabs, Torsten & Hans‐Jörg Schek. (2002). Generating Vector Spaces On-the-fly for Flexible XML Retrieval. 22 indexed citations
16.
Grabs, Torsten, Klemens Böhm, & Hans‐Jörg Schek. (2001). PowerDB-IR.
17.
Grabs, Torsten, Klemens Böhm, & Hans‐Jörg Schek. (2001). PowerDB-IR. 411–418. 21 indexed citations
18.
Grabs, Torsten, et al.. (2000). A parallel document engine built on top of a cluster of databases. Repository for Publications and Research Data (ETH Zurich). 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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