Hwee-Boon Low

403 citations
7 papers · 285 indexed · h-index 4
Journals
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. (1 paper)Computer Networks and ISDN Systems (1 paper)PubMed (1 paper)
Partner nations
Singapore

In The Last Decade

Hwee-Boon Low

5 papers receiving 258 citations

Peers

Hwee-Boon Low
Comparison fields: 5 of 46
  • Artificial Intelligence 244
  • Information Systems 122
  • Signal Processing 39
  • Computer Vision and Pattern Recognition 65
  • Communication 8
Replace Myung-Gil Jang with:
Myung-Gil Jang South Korea
Yunhua Hu China
Eric Crestan United States
Thomas Roelleke United Kingdom
Catherine Berrut France
John Broglio United States
Sarah Zelikovitz United States
R.D.J. Post Netherlands
Günter Ladwig Germany
Atulya Velivelli United States
Hwee-Boon Low relative to Myung-Gil Jang South Korea Myung-Gil Jang's profile →
Citations per field
00.5×1.5×1.9×
Myung-Gil Jang · 1×
Citations per year

Countries citing papers authored by Hwee-Boon Low

Since Specialization
Citations

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

Fields of papers citing papers by Hwee-Boon Low

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hwee-Boon Low. 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 Hwee-Boon Low. The network helps show where Hwee-Boon Low may publish in the future.

Co-authorship network

The 6 scholars most cited alongside Hwee-Boon Low, 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 Hwee-Boon Low Line = papers co-authored together Hwee-Boon Low links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 20123
2
Proposing a new term weighting scheme for text categorization
200664
3 200651
4 200591
5 200575
6 19980
7
Some Lessons Learnt by a New Comer
19931

About Hwee-Boon Low

Hwee-Boon Low is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Cell Biology and Molecular Biology, having authored 7 papers that have together received 285 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (4 papers), Advanced Text Analysis Techniques (2 papers), Web Data Mining and Analysis (2 papers), Algorithms and Data Compression (2 papers), Machine Learning in Bioinformatics (1 paper), Service-Oriented Architecture and Web Services (1 paper), Calpain Protease Function and Regulation (1 paper) and Signaling Pathways in Disease (1 paper). The work is most often cited by research in Artificial Intelligence (244 citations), Information Systems (122 citations), Signal Processing (39 citations), Computer Vision and Pattern Recognition (65 citations) and Communication (8 citations). Hwee-Boon Low has collaborated with scholars based in Singapore. Frequent co-authors include Man Lan, Chew-Lim Tan, Chew‐Lim Tan, Ji He, Lionel Wee and Ying Lü. Their work appears in journals such as Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., Computer Networks and ISDN Systems, PubMed and National University of Singapore.

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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