Phuc Do

557 total citations
47 papers, 253 citations indexed

About

Phuc Do is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics. According to data from OpenAlex, Phuc Do has authored 47 papers receiving a total of 253 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 19 papers in Information Systems and 19 papers in Statistical and Nonlinear Physics. Recurrent topics in Phuc Do's work include Complex Network Analysis Techniques (19 papers), Topic Modeling (17 papers) and Advanced Graph Neural Networks (17 papers). Phuc Do is often cited by papers focused on Complex Network Analysis Techniques (19 papers), Topic Modeling (17 papers) and Advanced Graph Neural Networks (17 papers). Phuc Do collaborates with scholars based in Vietnam, Myanmar and Poland. Phuc Do's co-authors include Phu Pham, Brij B. Gupta, Thuc D. Nguyen, Phuong Thi-Bich Le and Thanh Tran and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and Neural Computing and Applications.

In The Last Decade

Phuc Do

41 papers receiving 235 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Phuc Do Vietnam 9 203 74 44 35 20 47 253
Pavan Kapanipathi United States 12 323 1.6× 95 1.3× 53 1.2× 46 1.3× 24 1.2× 38 377
Hongkui Yu China 4 356 1.8× 104 1.4× 27 0.6× 44 1.3× 15 0.8× 9 430
Sion Jang South Korea 3 191 0.9× 77 1.0× 14 0.3× 27 0.8× 18 0.9× 4 250
Aurora Pons-Porrata Cuba 8 182 0.9× 87 1.2× 35 0.8× 26 0.7× 13 0.7× 12 247
Min-Chul Yang South Korea 8 217 1.1× 116 1.6× 48 1.1× 37 1.1× 40 2.0× 12 274
Koji Eguchi Japan 10 341 1.7× 203 2.7× 21 0.5× 60 1.7× 14 0.7× 59 425
Cheol-Young Ock South Korea 9 219 1.1× 55 0.7× 10 0.2× 29 0.8× 16 0.8× 38 260
Peifeng Li China 10 315 1.6× 79 1.1× 46 1.0× 35 1.0× 71 3.5× 79 391
Victor E. Lee United States 6 98 0.5× 106 1.4× 16 0.4× 46 1.3× 32 1.6× 8 188
Tereza Iofciu Germany 7 151 0.7× 117 1.6× 27 0.6× 27 0.8× 12 0.6× 14 206

Countries citing papers authored by Phuc Do

Since Specialization
Citations

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

Fields of papers citing papers by Phuc Do

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Phuc Do

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

All Works

20 of 20 papers shown
1.
Do, Phuc, et al.. (2025). A Novel Multi-hop Query Answering System Based on a Large Knowledge Graph and Distributed Computing. ACM Transactions on Asian and Low-Resource Language Information Processing. 24(3). 1–28.
2.
Do, Phuc, et al.. (2023). A novel framework to enhance the performance of training distributed deep neural networks. Intelligent Data Analysis. 27(3). 753–768.
3.
Do, Phuc, et al.. (2023). Fake news detection using knowledge graph and graph convolutional network. Journal of Intelligent & Fuzzy Systems. 45(6). 11107–11119.
4.
Do, Phuc, et al.. (2021). Embedding knowledge on ontology into the corpus by topic to improve the performance of deep learning methods in sentiment analysis. Scientific Reports. 11(1). 23541–23541. 5 indexed citations
5.
Pham, Phu, et al.. (2021). Automatic topic labelling for text document using ontology of graph-based concepts and dependency graph. International Journal of Business Information Systems. 36(2). 221–221. 1 indexed citations
6.
Do, Phuc & Phu Pham. (2021). W-KG2Vec: a weighted text-enhanced meta-path-based knowledge graph embedding for similarity search. Neural Computing and Applications. 33(23). 16533–16555. 4 indexed citations
7.
Pham, Phu & Phuc Do. (2021). W-MMP2Vec: Topic-driven network embedding model for link prediction in content-based heterogeneous information network. Intelligent Data Analysis. 25(3). 711–738. 4 indexed citations
8.
9.
Do, Phuc, et al.. (2020). DMTree: A Novel Indexing Method for Finding Similarities in Large Vector Sets. International Journal of Advanced Computer Science and Applications. 11(4). 3 indexed citations
10.
Do, Phuc, et al.. (2020). Building a knowledge graph by using cross-lingual transfer method and distributed MinIE algorithm on apache spark. Neural Computing and Applications. 34(11). 8393–8409. 15 indexed citations
11.
Pham, Phu & Phuc Do. (2020). W-Com2Vec: A topic-driven meta-path- based intra-community embedding for content-based heterogeneous information network. Intelligent Data Analysis. 24(5). 1207–1233. 3 indexed citations
12.
Pham, Phu & Phuc Do. (2019). W-MetaPath2Vec: The topic-driven meta-path-based model for large-scaled content-based heterogeneous information network representation learning. Expert Systems with Applications. 123. 328–344. 23 indexed citations
13.
Nguyen, Thuc D. & Phuc Do. (2018). CitationLDA++. 31–37. 3 indexed citations
14.
Pham, Phu & Phuc Do. (2018). Topic-driven top-k similarity search by applying constrained meta-path based in content-based schema-enriched heterogeneous information network. International Journal of Business Intelligence and Data Mining. 1(1). 1–1. 1 indexed citations
15.
Do, Phuc, et al.. (2018). Social Network Analysis Based on Topic Model with Temporal Factor. International Journal of Knowledge and Systems Science. 9(1). 82–97. 9 indexed citations
16.
Nguyen, Thuc D. & Phuc Do. (2017). Managing and Visualizing Citation Network Using Graph Database and LDA Model. 100–105. 3 indexed citations
17.
Tran, Thanh, et al.. (2015). Detecting Communities and Surveying the Most Influence of Online Users. 4(6). 172–178. 1 indexed citations
18.
19.
Do, Phuc, et al.. (2013). Topic based object Influence analysis in Social networks. Science and Technology Development Journal. 16(4). 68–78. 1 indexed citations
20.

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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