Chuck Bear

502 citations
7 papers · 289 · h-index 6

Impact in

Papers in

Chuck Bear

6 papers receiving 255 citations

Peers

Chuck Bear
Comparison fields: 5 of 24
  • Computer Networks and Communications 249
  • Signal Processing 95
  • Information Systems 122
  • Hardware and Architecture 30
  • Information Systems and Management 20
Replace Stratos Papadomanolakis with:
Stratos Papadomanolakis United States
Philipp Unterbrunner Switzerland
Thierry Cruanes United States
Manolis M. Tsangaris United States
Mert Akdere United States
Benoît Dageville United States
Jeff LeFevre United States
Karl Dias United States
Andrew Witkowski United States
Berni Schiefer United States
Chuck Bear relative to Stratos Papadomanolakis United States Stratos Papadomanolakis's profile →
Citations per field
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Stratos Papadomanolakis · 1×
Citations per year

Countries citing papers authored by Chuck Bear

Since Specialization
Citations

This map shows the geographic impact of Chuck Bear'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 Chuck Bear with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chuck Bear more than expected).

Fields of papers citing papers by Chuck Bear

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chuck Bear. 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 Chuck Bear. The network helps show where Chuck Bear may publish in the future.

Co-authors

The 17 scholars most cited alongside Chuck Bear, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chuck Bear Line = papers co-authored together Chuck Bear links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2012190
2
One Size Fits All? Part 2: Benchmarking Studies.
200732
3
One Size Fits All? - Part 2: Benchmarking Results
200724
4 201318
5 202017
6 20128
7 20190

About Chuck Bear

Chuck Bear is a scholar working on Computer Networks and Communications, Signal Processing, Artificial Intelligence, Information Systems and Information Systems and Management, having authored 7 papers that have together received 289 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (6 papers), Data Management and Algorithms (5 papers), Semantic Web and Ontologies (2 papers), Scientific Computing and Data Management (1 paper), Cloud Computing and Resource Management (1 paper), Data Mining Algorithms and Applications (1 paper), Algorithms and Data Compression (1 paper) and Data Quality and Management (1 paper). The work is most often cited by research in Computer Networks and Communications (249 citations), Signal Processing (95 citations), Information Systems (122 citations), Hardware and Architecture (30 citations) and Information Systems and Management (20 citations). Chuck Bear has collaborated with scholars based in United States. Frequent co-authors include Nga Tran, Ramakrishna Varadarajan, Andrew Lamb, Matt Fuller, John Lifter, Jennie Rogers, Stavros Harizopoulos, Nabil Hachem, Michael Stonebraker and Mitch Cherniack. Their work appears in journals such as Proceedings of the VLDB Endowment and Conference on Innovative Data Systems Research.

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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