Ladda Suanmali
- Artificial Intelligence top 5%
- Information Systems
- Safety Research
- Management Science and Operations Research
- Computer Vision and Pattern Recognition
- Co-authors
- Naomie SalimMohammed Salem BinwahlanAhmed Hamza OsmanSalha M. AlzahraniOkfalisaMegawati MegawatiSaktioto Saktioto
- Topics
- Natural Language Processing Techniques (13 papers)Topic Modeling (13 papers)Advanced Text Analysis Techniques (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaInformation Processing & ManagementJournal of Applied Sciences
In The Last Decade
Ladda Suanmali
15 papers receiving 258 citations
Peers
Comparison fields: 5 of 22
- Artificial Intelligence 275
- Information Systems 36
- Safety Research 15
- Management Science and Operations Research 8
- Computer Vision and Pattern Recognition 5
Countries citing papers authored by Ladda Suanmali
This map shows the geographic impact of Ladda Suanmali'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 Ladda Suanmali with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ladda Suanmali more than expected).
Fields of papers citing papers by Ladda Suanmali
This network shows the impact of papers produced by Ladda Suanmali. 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 Ladda Suanmali. The network helps show where Ladda Suanmali may publish in the future.
Co-authorship network of co-authors of Ladda Suanmali
This figure shows the co-authorship network connecting the top 25 collaborators of Ladda Suanmali. A scholar is included among the top collaborators of Ladda Suanmali 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 Ladda Suanmali. Ladda Suanmali is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 17 | |
| 3 | Pseudo genetic and probabilistic-based feature selection method for extractive single document summarization | 4 |
| 4 | 21 | |
| 5 | 47 | |
| 6 | 9 | |
| 7 | 3 | |
| 8 | 13 | |
| 9 | 44 | |
| 10 | MMI diversity based text summarization | 11 |
| 11 | Swarm based features selection for text summarization | 28 |
| 12 | 42 | |
| 13 | 25 | |
| 14 | 4 | |
| 15 | Automatic text summarization using feature based fuzzy extraction | 13 |
About Ladda Suanmali
Ladda Suanmali is a scholar working on Artificial Intelligence, Information Systems and Infectious Diseases, having authored 15 papers that have together received 283 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (13 papers), Topic Modeling (13 papers) and Advanced Text Analysis Techniques (12 papers). The work is most often cited by research in Artificial Intelligence (275 citations), Safety Research (15 citations) and Information Systems (36 citations). Ladda Suanmali has collaborated with scholars based in Malaysia, Thailand and Yemen. Frequent co-authors include Naomie Salim, Mohammed Salem Binwahlan, Ahmed Hamza Osman, Salha M. Alzahrani, Okfalisa, Megawati Megawati and Saktioto Saktioto. Their work appears in journals such as SHILAP Revista de lepidopterología, Information Processing & Management and Journal of Applied Sciences.
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.