Na-Rae Han

24 papers receiving 457 citations

Peers

Na-Rae Han
Comparison fields: 5 of 61
  • Artificial Intelligence 399
  • Developmental and Educational Psychology 59
  • Education 59
  • Language and Linguistics 53
  • Information Systems 34
Replace Geoffrey T. LaFlair with:
Geoffrey T. LaFlair United States
Anastassia Loukina United States
Masaki Eguchi United States
Yanfang Su Hong Kong
Alistair Van Moere United States
Jeffrey Stewart Japan
Kanglong Liu Hong Kong
Yosuke Sasao Japan
Gregory Aist United States
César González-Ferreras Spain
Na-Rae Han relative to Geoffrey T. LaFlair United States Geoffrey T. LaFlair's profile →
Citations per field
00.5×3.6×
Geoffrey T. LaFlair · 1×
Citations per year

Countries citing papers authored by Na-Rae Han

Since Specialization
Citations

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

Fields of papers citing papers by Na-Rae Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Na-Rae Han. 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 Na-Rae Han. The network helps show where Na-Rae Han may publish in the future.

Co-authorship network of co-authors of Na-Rae Han

This figure shows the co-authorship network connecting the top 25 collaborators of Na-Rae Han. A scholar is included among the top collaborators of Na-Rae Han 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 Na-Rae Han. Na-Rae Han 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
#WorkIndexed citations
1 5
2 22
3
K-SNACS: Annotating Korean Adposition Semantics
2
4 3
5
Building Universal Dependency Treebanks in Korean
17
6
Accurate Measurement of Lexical Sophistication with Reference to ESL Learner Data.
4
7
Parser combinators for Tigrinya and Oromo morphology
1
8 58
9
Using an Error-Annotated Learner Corpus to Develop an ESL/EFL Error Correction System.
38
10 3
11 1
12
The Development of a Communication Course for RN-BSN Students
1
13
Klex: A Finite-State Transducer Lexicon of Korean
1
14 110
15
Korean zero pronouns: analysis and resolution
25
16
Guidelines for Penn Korean Treebank Version 2.0
4
17
Detecting Errors in English Article Usage with a Maximum Entropy Classifier Trained on a Large, Diverse Corpus.
29
18 1
19
Part of Speech Tagging Guidelines for Penn Korean Treebank
5
20
Bracketing Guidelines for Penn Korean TreeBank
14

About Na-Rae Han

Na-Rae Han is a scholar working on Leadership and Management, Artificial Intelligence and Developmental and Educational Psychology, having authored 24 papers that have together received 524 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (18 papers), Topic Modeling (11 papers) and Text Readability and Simplification (8 papers). The work is most often cited by research in Artificial Intelligence (399 citations), Research and Theory (6 citations) and Leadership and Management (8 citations). Na-Rae Han has collaborated with scholars based in United States, South Korea and Japan. Frequent co-authors include Martin Chodorow, Claudia Leacock, Joel Tetreault, Carolyn Feher Waltz, Louise S. Jenkins, Jena D. Hwang, Ellen F. Prince, Martha Palmer, Chung–hye Han and Jinho D. Choi. Their work appears in journals such as Journal of Medical Internet Research, Language Resources and Evaluation and Natural Language Engineering.

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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