Kinam Park

491 citations
28 papers · 322 · h-index 7

Impact in

    • Spam and Phishing Detection
    • Topic Modeling
    • Sentiment Analysis and Opinion Mining
    • Internet Traffic Analysis and Secure E-voting
    • Natural Language Processing Techniques

Papers in

    • Topic Modeling 12
    • Natural Language Processing Techniques 8
    • Advanced Text Analysis Techniques 5
    • Sentiment Analysis and Opinion Mining 2
    • Web Data Mining and Analysis 4
    • Information Retrieval and Search Behavior 3
    • Spam and Phishing Detection 2

Kinam Park

24 papers receiving 303 citations

Peers

Kinam Park
Comparison fields: 5 of 47
  • Information Systems 156
  • Artificial Intelligence 194
  • Signal Processing 62
  • Health Informatics 5
  • Sociology and Political Science 150
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Citations per field
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Citations per year

Countries citing papers authored by Kinam Park

Since Specialization
Citations

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

Fields of papers citing papers by Kinam Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Kinam Park, 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 Kinam Park Line = papers co-authored together Kinam Park links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019177
2 201847
3 201419
4 202018
5 201510
6 20117
7 20226
8 20175
9 20104
10 20173
11 20173
12 20133
13 20133
14 20173
15 20222
16 20222
17
CopyCaptor: PPlagiarized source retrieval system using global word frequency and local feedback: Notebook for PAN at CLEF 2013
20132
18
CopyCaptor : Plagiarized Source Retrieval System using Global Word Frequency and Local Feedback Notebook for PAN at CLEF 2013.
20131
19
A Study on Building Korean Dialogue Corpus for Restaurant reservation and recommendation
20181
20 20161

About Kinam Park

Kinam Park is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Molecular Biology and Computer Networks and Communications, having authored 28 papers that have together received 322 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (8 papers), Advanced Text Analysis Techniques (5 papers), Web Data Mining and Analysis (4 papers), Biomedical Text Mining and Ontologies (3 papers), Information Retrieval and Search Behavior (3 papers), Spam and Phishing Detection (2 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Information Systems (156 citations), Artificial Intelligence (194 citations), Signal Processing (62 citations), Health Informatics (5 citations) and Sociology and Political Science (150 citations). Kinam Park has collaborated with scholars based in South Korea and Estonia. Frequent co-authors include Heuiseok Lim, Yun-Gyung Cheong, Chanjun Park, Jaechoon Jo, Yeongwook Yang, Taemin Lee, Soonyoung Jung, Byung-Chull Bae, Younghee Jung and Woohyun Park. Their work appears in journals such as Electronics, Applied Sciences, Indian Journal of Science and Technology, Wireless Personal Communications and Knowledge-Based Systems.

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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