Ngo Xuan Bach
- Artificial Intelligence top 5%
- Information Systems top 10%
- Political Science and International Relations top 10%
- Computer Vision and Pattern Recognition
- Management Science and Operations Research
- Co-authors
- Từ Minh PhươngLe-Minh NguyenAkira ShimazuTran Cong ThanhNguyễn Thị Thanh ThủyHa-Thanh NguyenVu TranKunihiko Hiraishi
- Topics
- Topic Modeling (24 papers)Natural Language Processing Techniques (18 papers)Sentiment Analysis and Opinion Mining (9 papers)
In The Last Decade
Ngo Xuan Bach
30 papers receiving 281 citations
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 247
- Information Systems 98
- Political Science and International Relations 45
- Computer Vision and Pattern Recognition 28
- Management Science and Operations Research 23
Countries citing papers authored by Ngo Xuan Bach
This map shows the geographic impact of Ngo Xuan Bach'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 Ngo Xuan Bach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ngo Xuan Bach more than expected).
Fields of papers citing papers by Ngo Xuan Bach
This network shows the impact of papers produced by Ngo Xuan Bach. 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 Ngo Xuan Bach. The network helps show where Ngo Xuan Bach may publish in the future.
Co-authorship network of co-authors of Ngo Xuan Bach
This figure shows the co-authorship network connecting the top 25 collaborators of Ngo Xuan Bach. A scholar is included among the top collaborators of Ngo Xuan Bach 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 Ngo Xuan Bach. Ngo Xuan Bach 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 | 2 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 5 | |
| 7 | 14 | |
| 8 | 24 | |
| 9 | 2 | |
| 10 | 39 | |
| 11 | 20 | |
| 12 | 4 | |
| 13 | 11 | |
| 14 | 22 | |
| 15 | 13 | |
| 16 | A Reranking Model for Discourse Segmentation using Subtree Features | 17 |
| 17 | Supervised and Semi-Supervised Sequence Learning for Recognition of Requisite Part and Effectuation Part in Law Sentences | 4 |
| 18 | 8 | |
| 19 | Learning Logical Structures of Paragraphs in Legal Articles | 1 |
| 20 | 4 |
About Ngo Xuan Bach
Ngo Xuan Bach is a scholar working on Artificial Intelligence, Information Systems and Political Science and International Relations, having authored 31 papers that have together received 301 indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Natural Language Processing Techniques (18 papers) and Sentiment Analysis and Opinion Mining (9 papers). The work is most often cited by research in Artificial Intelligence (247 citations), Information Systems (98 citations) and Political Science and International Relations (45 citations). Ngo Xuan Bach has collaborated with scholars based in Vietnam, Japan and Slovakia. Frequent co-authors include Từ Minh Phương, Le-Minh Nguyen, Akira Shimazu, Tran Cong Thanh, Nguyễn Thị Thanh Thủy, Ha-Thanh Nguyen, Vu Tran, Kunihiko Hiraishi, Trung Hai Nguyen and Hoang-Anh Pham. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Information 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.