Dae Hoon Park

26 total papers · 557 total citations
16 papers, 279 citations indexed

About

Dae Hoon Park is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Dae Hoon Park has authored 16 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 5 papers in Information Systems and 2 papers in Computer Networks and Communications. Recurrent topics in Dae Hoon Park's work include Advanced Text Analysis Techniques (7 papers), Topic Modeling (6 papers) and Sentiment Analysis and Opinion Mining (4 papers). Dae Hoon Park is often cited by papers focused on Advanced Text Analysis Techniques (7 papers), Topic Modeling (6 papers) and Sentiment Analysis and Opinion Mining (4 papers). Dae Hoon Park collaborates with scholars based in United States, China and South Korea. Dae Hoon Park's co-authors include ChengXiang Zhai, Mengwen Liu, Catherine Blake, Hyun Duk Kim, Yi Fang, Haohong Wang, ChengXiang Zhai, Yue Lu, Young Joon Hong and Han S. Uhm and has published in prestigious journals such as Information Processing & Management, Plasma Processes and Polymers and Information Retrieval.

In The Last Decade

Dae Hoon Park

16 papers receiving 266 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Dae Hoon Park	143	105	57	42	29	16	279
Siham Yousfi	197 1.4×	54 0.5×	9 0.2×	24 0.6×	26 0.9×	15	321
Sasidhar Babu Suvanam	97 0.7×	85 0.8×	9 0.2×	24 0.6×	14 0.5×	13	304
Naveed Hussain	147 1.0×	158 1.5×	21 0.4×	8 0.2×	55 1.9×	15	253
Mala Dutta	93 0.7×	128 1.2×	4 0.1×	19 0.5×	34 1.2×	18	267
A S M Touhidul Hasan	139 1.0×	96 0.9×	9 0.2×	12 0.3×	47 1.6×	24	235
Yikun Xian	161 1.1×	111 1.1×	27 0.5×	9 0.2×	23 0.8×	17	236
Jörg Schlötterer	214 1.5×	35 0.3×	15 0.3×	5 0.1×	16 0.6×	24	320
Milad Ahmadian	178 1.2×	163 1.6×	43 0.8×	16 0.4×	17 0.6×	11	295
Avishek Garain	219 1.5×	75 0.7×	33 0.6×	12 0.3×	61 2.1×	18	325
Deepjyoti Roy	92 0.6×	117 1.1×	4 0.1×	14 0.3×	34 1.2×	12	245

Countries citing papers authored by Dae Hoon Park

Since Specialization

Citations

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

Fields of papers citing papers by Dae Hoon Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae Hoon Park. 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 Dae Hoon Park. The network helps show where Dae Hoon Park may publish in the future.

Co-authorship network of co-authors of Dae Hoon Park

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

All Works

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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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