Neal Sample

479 citations
17 papers · 359 · h-index 7

Impact in

Papers in

Neal Sample

17 papers receiving 321 citations

Peers

Neal Sample
Comparison fields: 5 of 29
  • Signal Processing 237
  • Computer Networks and Communications 312
  • Artificial Intelligence 200
  • Information Systems 122
  • Hardware and Architecture 15
Replace Mohamed Ziauddin with:
Mohamed Ziauddin United States
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Mert Akdere United States
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Laurent Mignet India
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Curt J. Ellmann United States
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Citations per field
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Citations per year

Countries citing papers authored by Neal Sample

Since Specialization
Citations

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

Fields of papers citing papers by Neal Sample

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Neal Sample, 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 Neal Sample Line = papers co-authored together Neal Sample links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
A Fast Index for Semistructured Data
2001248
2 200232
3 200215
4 199912
5
Composition of Multi-site Services
199911
6
Optimizing Search Strategies in k-d Trees
20018
7 20028
8 19994
9 20024
10 19993
11 20033
12 20033
13
Pipeline Expansion in Coordinated Applications.
19992
14 20012
15 20002
16
Hybrid Search for Optimization of High-Dimensional k-d Trees
19991
17 20031

About Neal Sample

Neal Sample is a scholar working on Computer Networks and Communications, Artificial Intelligence, Information Systems, Signal Processing and Information Systems and Management, having authored 17 papers that have together received 359 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (6 papers), Data Management and Algorithms (6 papers), Distributed and Parallel Computing Systems (5 papers), Algorithms and Data Compression (3 papers), Service-Oriented Architecture and Web Services (3 papers), Scientific Computing and Data Management (3 papers), Advanced Software Engineering Methodologies (3 papers) and Distributed systems and fault tolerance (3 papers). The work is most often cited by research in Signal Processing (237 citations), Computer Networks and Communications (312 citations), Artificial Intelligence (200 citations), Information Systems (122 citations) and Hardware and Architecture (15 citations). Neal Sample has collaborated with scholars based in United States and France. Frequent co-authors include Brian F. Cooper, Michael J. Franklin, Gı́sli R. Hjaltason, Gio Wiederhold, Mark G. Arnold, Timothy J. Purcell and L. F. Cohen. Their work appears in journals such as World Wide Web, Lecture notes in computer science, Notes on numerical fluid mechanics and multidisciplinary design, ACM SIGSOFT Software Engineering Notes and Very Large Data Bases.

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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