Dan Smith

823 citations
37 papers · 486 indexed · h-index 8
Topics
Semantic Web and Ontologies (5 papers)Advanced Database Systems and Queries (4 papers)Advanced Image and Video Retrieval Techniques (4 papers)

In The Last Decade

Dan Smith

30 papers receiving 435 citations

Peers

Dan Smith
Comparison fields: 5 of 114
  • Signal Processing 146
  • Computer Vision and Pattern Recognition 110
  • Ecology 97
  • Molecular Biology 79
  • Artificial Intelligence 73
Replace Xiao Xie with:
Xiao Xie China
Yves Bédard Canada
Timo Kaukoranta Finland
Ali Zeeshan Ijaz Pakistan
Xiaojie Wang China
Florence Le Ber France
P. Nye United States
Zhangliang Chen China
Dan Smith relative to Xiao Xie China Xiao Xie's profile →
Citations per field
00.5×2.6×
Xiao Xie · 1×
Citations per year

Countries citing papers authored by Dan Smith

Since Specialization
Citations

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

Fields of papers citing papers by Dan Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Smith. A scholar is included among the top collaborators of Dan Smith 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 Dan Smith. Dan Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 2
3 1
4 1
5 2
6 1
7 10
8
Web searching behaviour for academic resources
3
9
Powering Official Statistics at Statistics New Zealand with DDI-L and Colectica: a case study
1
10 1
11
An efficient strategy for implementing iterative area openings using the max tree
2
12
An efficient implementation of max tree with linked list and hash table
6
13 40
14 1
15 5
16
A Coordination Model for Workflow Management Systems.
1
17 25
18 7
19
Information finding and filtering for collections of semi-structured documents.
1
20 1

About Dan Smith

Dan Smith is a scholar working on Library and Information Sciences, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 37 papers that have together received 486 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (5 papers), Advanced Database Systems and Queries (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Signal Processing (146 citations), Developmental Biology (16 citations) and Computer Vision and Pattern Recognition (110 citations). Dan Smith has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Ling Ma, Ben Milner, Eric W. Triplett, Angela D. Kent, Barbara J. Benson, Janani Vivekananda, Janpeter Schilling, Richard Harvey, Nick Ryan and Mark Fisher. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied and Environmental Microbiology and Canadian Journal of Forest 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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