Thabo Semong

1.2k citations
16 papers · 681 · 1 hit paper · h-index 7

Impact in

Papers in

Thabo Semong

16 papers receiving 661 citations

Thabo Semong's Hit Papers

A survey on missing data in machine learning 2021 · 513 citations
5130+1+3Years since publication100200300400500

Peers

Thabo Semong
Comparison fields: 5 of 141
  • Computational Mathematics 16
  • Health Informatics 10
  • Health Information Management 33
  • Artificial Intelligence 220
  • Computer Networks and Communications 139
Replace André Gonçalves with:
André Gonçalves United States
Vipin Kumar India
Thabiso Maupong Botswana
Dimane Mpoeleng Botswana
Banyatsang Mphago Botswana
Oteng Tabona Botswana
José‐Luis Sancho‐Gómez Spain
Roberto Corizzo United States
Maximilian Schleich United Kingdom
André Luis Debiaso Rossi Brazil
Thabo Semong relative to André Gonçalves United States André Gonçalves's profile →
Citations per field
00.5×2.7×
André Gonçalves · 1×
Citations per year

Countries citing papers authored by Thabo Semong

Since Specialization
Citations

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

Fields of papers citing papers by Thabo Semong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Thabo Semong, 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 Thabo Semong Line = papers co-authored together Thabo Semong links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
A survey on missing data in machine learning
Hit paper breakdown →
2021513
2 202050
3 201947
4 201717
5 202115
6 201911
7 201910
8 20204
9 20183
10 20093
11 20202
12 20222
13 20231
14 20241
15 20221
16 20191

About Thabo Semong

Thabo Semong is a scholar working on Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering, Information Systems and Signal Processing, having authored 16 papers that have together received 681 indexed citations. Recurring topics across this work include Software-Defined Networks and 5G (6 papers), Caching and Content Delivery (5 papers), Privacy-Preserving Technologies in Data (3 papers), Advanced Optical Network Technologies (2 papers), Energy Efficient Wireless Sensor Networks (2 papers), Digital and Cyber Forensics (2 papers), Network Traffic and Congestion Control (2 papers) and IoT and Edge/Fog Computing (2 papers). The work is most often cited by research in Computational Mathematics (16 citations), Health Informatics (10 citations), Health Information Management (33 citations), Artificial Intelligence (220 citations) and Computer Networks and Communications (139 citations). Thabo Semong has collaborated with scholars based in Botswana, China and United Kingdom. Frequent co-authors include Thabiso Maupong, Banyatsang Mphago, Dimane Mpoeleng, Oteng Tabona, Kun Xie, Shiming He, Lele Wang, Huibin Zhou, Hongyang Chen and Zhu Xiao. Their work appears in journals such as Electronics, IEEE Access, IEEE Transactions on Cybernetics, Scientific African and Evolutionary Intelligence.

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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