Yew Ken Chia

38 total papers · 517 total citations
11 papers, 193 citations indexed

About

Yew Ken Chia is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Yew Ken Chia has authored 11 papers receiving a total of 193 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Molecular Biology. Recurrent topics in Yew Ken Chia's work include Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Sentiment Analysis and Opinion Mining (2 papers). Yew Ken Chia is often cited by papers focused on Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Sentiment Analysis and Opinion Mining (2 papers). Yew Ken Chia collaborates with scholars based in Singapore, Cayman Islands and United States. Yew Ken Chia's co-authors include Lidong Bing, Lu Xu, Shafiq Joty, Linlin Liu, Chengwei Qin, Boyang Li, Bosheng Ding, Soujanya Poria, Luo Si and Qingyu Tan and has published in prestigious journals such as Sensors.

In The Last Decade

Yew Ken Chia

9 papers receiving 187 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yew Ken Chia 175 21 14 9 5 11 193
Katherine A. Keith 98 0.6× 14 0.7× 20 1.4× 9 1.0× 10 2.0× 9 242
Alon Halfon 138 0.8× 22 1.0× 12 0.9× 10 1.1× 7 1.4× 11 166
Alex Marin 184 1.1× 24 1.1× 19 1.4× 5 0.6× 8 1.6× 20 207
Gabriele Pergola 215 1.2× 21 1.0× 15 1.1× 7 0.8× 8 1.6× 21 241
Vasileios Iosifidis 132 0.8× 16 0.8× 11 0.8× 6 0.7× 11 2.2× 7 174
Dennis Diefenbach 178 1.0× 31 1.5× 16 1.1× 19 2.1× 3 0.6× 8 191
Ariel Gera 125 0.7× 25 1.2× 9 0.6× 9 1.0× 6 1.2× 12 152
Yunlong Liang 180 1.0× 26 1.2× 31 2.2× 20 2.2× 5 1.0× 17 216
Johnny Tian-Zheng Wei 249 1.4× 27 1.3× 49 3.5× 4 0.4× 4 0.8× 11 264
Mohsen Mesgar 180 1.0× 26 1.2× 11 0.8× 6 0.7× 6 1.2× 16 192

Countries citing papers authored by Yew Ken Chia

Since Specialization
Citations

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

Fields of papers citing papers by Yew Ken Chia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yew Ken Chia. 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 Yew Ken Chia. The network helps show where Yew Ken Chia may publish in the future.

Co-authorship network of co-authors of Yew Ken Chia

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

All Works

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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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