Long Duong

1.0k citations
18 papers · 566 indexed · h-index 13
Journals
Ecological Informatics (1 paper)International Joint Conference on Natural Language Processing (1 paper)Meeting of the Association for Computational Linguistics (1 paper)

In The Last Decade

Long Duong

18 papers receiving 506 citations

Peers

Long Duong
Comparison fields: 5 of 76
  • Artificial Intelligence 474
  • Computer Vision and Pattern Recognition 125
  • Information Systems 46
  • Computational Mathematics 1
  • Signal Processing 17
Replace Martin Popel with:
Martin Popel Czechia
Annette Rios Switzerland
Zuchao Li China
Jie Fu China
Ledell Wu China
Chenhui Chu Japan
Joachim Bingel Denmark
Yujuan Ding Hong Kong
Long Duong relative to Martin Popel Czechia Martin Popel's profile →
Citations per field
00.5×1.5×1.9×
Martin Popel · 1×
Citations per year

Countries citing papers authored by Long Duong

Since Specialization
Citations

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

Fields of papers citing papers by Long Duong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Long Duong, 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 Long Duong Line = papers co-authored together Long Duong links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 20241
2 20194
3 201817
4 201725
5 201721
6 201612
7 201659
8 201613
9 20168
10 201680
11 2015219
12 201527
13 201527
14
Automatic Identification of Expressions of Locations in Tweet Messages using Conditional Random Fields
20141
15 201418
16 201417
17
Simpler unsupervised POS tagging with bilingual projections
201314
18
Increasing the Quality and Quantity of Source Language Data for Unsupervised Cross-Lingual POS Tagging
20133

About Long Duong

Long Duong is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Oceanography and Nature and Landscape Conservation, having authored 18 papers that have together received 566 indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Natural Language Processing Techniques (15 papers), Text Readability and Simplification (4 papers), Speech and dialogue systems (3 papers), Speech Recognition and Synthesis (2 papers), Spam and Phishing Detection (1 paper), Speech and Audio Processing (1 paper) and Expert finding and Q&A systems (1 paper). The work is most often cited by research in Artificial Intelligence (474 citations), Computer Vision and Pattern Recognition (125 citations), Information Systems (46 citations), Computational Mathematics (1 citation) and Signal Processing (17 citations). Long Duong has collaborated with scholars based in Australia, United States and Czechia. Frequent co-authors include Steven Bird, Trevor Cohn, Paul Cook, Antonios Anastasopoulos, David Chiang, Hiroshi Kanayama, Tengfei Ma, Mark Johnson, Philip R. Cohen and Dominique Estival. Their work appears in journals such as Ecological Informatics, International Joint Conference on Natural Language Processing and Meeting of the Association for Computational Linguistics.

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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