Eun Young Ha

606 total citations
22 papers, 308 citations indexed

About

Eun Young Ha is a scholar working on Artificial Intelligence, Developmental and Educational Psychology and Social Psychology. According to data from OpenAlex, Eun Young Ha has authored 22 papers receiving a total of 308 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 7 papers in Developmental and Educational Psychology and 2 papers in Social Psychology. Recurrent topics in Eun Young Ha's work include Intelligent Tutoring Systems and Adaptive Learning (11 papers), Topic Modeling (11 papers) and Speech and dialogue systems (9 papers). Eun Young Ha is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (11 papers), Topic Modeling (11 papers) and Speech and dialogue systems (9 papers). Eun Young Ha collaborates with scholars based in United States and South Korea. Eun Young Ha's co-authors include James C. Lester, Kristy Elizabeth Boyer, Bradford Mott, Jonathan Rowe, Robert Phillips, Michael D. Wallis, Mladen A. Vouk, Joseph F. Grafsgaard, Wookhee Min and Jennifer Sabourin and has published in prestigious journals such as AI Magazine, International Journal of Artificial Intelligence in Education and Clinical Hemorheology and Microcirculation.

In The Last Decade

Eun Young Ha

22 papers receiving 292 citations

Peers

Eun Young Ha
Keith Brawner United States
Sidney D’Mello United States
Severin Klingler Switzerland
Borhan Samei United States
Heather Maclaren Canada
Maria Moundridou Greece
Sangho Suh Canada
Grégory Dyke France
Cord Hockemeyer Austria
Andrew Emerson United States
Keith Brawner United States
Eun Young Ha
Citations per year, relative to Eun Young Ha Eun Young Ha (= 1×) peers Keith Brawner

Countries citing papers authored by Eun Young Ha

Since Specialization
Citations

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

Fields of papers citing papers by Eun Young Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eun Young Ha. 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 Eun Young Ha. The network helps show where Eun Young Ha may publish in the future.

Co-authorship network of co-authors of Eun Young Ha

This figure shows the co-authorship network connecting the top 25 collaborators of Eun Young Ha. A scholar is included among the top collaborators of Eun Young Ha 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 Eun Young Ha. Eun Young Ha 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.
Choi, Jimi, Eun Young Ha, Seung Min Chung, et al.. (2022). Critical shear stress of red blood cells as a novel integrated biomarker for screening chronic kidney diseases in cases of type 2 diabetes. Clinical Hemorheology and Microcirculation. 81(4). 293–303. 1 indexed citations
2.
Ha, Eun Young, Jonathan E. Rowe, Bradford Mott, & James Lester. (2021). Goal Recognition with Markov Logic Networks for Player-Adaptive Games. Proceedings of the AAAI Conference on Artificial Intelligence. 26(1). 2113–2119. 3 indexed citations
3.
Wiggins, Joseph B., Kristy Elizabeth Boyer, Aysu Ezen-Can, et al.. (2015). JavaTutor. 599–599. 22 indexed citations
4.
Min, Wookhee, Eun Young Ha, Jonathan Rowe, Bradford Mott, & James C. Lester. (2014). Deep Learning-Based Goal Recognition in Open-Ended Digital Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 10(1). 37–43. 38 indexed citations
5.
Ha, Eun Young, et al.. (2013). Learning Dialogue Management Models for Task-Oriented Dialogue with Parallel Dialogue and Task Streams. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 204–213. 3 indexed citations
6.
Ha, Eun Young, et al.. (2013). Learner characteristics and dialogue: recognising effective and student-adaptive tutorial strategies. International Journal of Learning Technology. 8(4). 382–382. 7 indexed citations
7.
Lester, James C., Eun Young Ha, Seung Y. Lee, et al.. (2013). Serious Games Get Smart: Intelligent Game‐Based Learning Environments. AI Magazine. 34(4). 31–45. 42 indexed citations
8.
Ha, Eun Young, et al.. (2012). Recognizing Effective and Student-Adaptive Tutor Moves in Task-Oriented Tutorial Dialogue. The Florida AI Research Society. 4 indexed citations
9.
Ha, Eun Young, et al.. (2012). Combining Verbal and Nonverbal Features to Overcome the ``Information Gap'' in Task-Oriented Dialogue. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 247–256. 13 indexed citations
10.
Kim, Ji-Young, et al.. (2012). Material Analysis and Deterioration Evaluation of Foundation Stones and Holy Stone Relics in Myeongdongseongdang Cathedral, Korea. Journal of Conservation Science. 28(4). 305–319. 5 indexed citations
11.
Boyer, Kristy Elizabeth, Eun Young Ha, Robert Phillips, & James C. Lester. (2011). The Impact of Task-Oriented Feature Sets on HMMs for Dialogue Modeling. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 49–58. 2 indexed citations
12.
Boyer, Kristy Elizabeth, Joseph F. Grafsgaard, Eun Young Ha, Robert Phillips, & James C. Lester. (2011). An Affect-Enriched Dialogue Act Classification Model for Task-Oriented Dialogue. Meeting of the Association for Computational Linguistics. 1190–1199. 20 indexed citations
13.
Ha, Eun Young, Jonathan Rowe, Bradford Mott, & James Lester. (2011). Goal Recognition with Markov Logic Networks for Player-Adaptive Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 7(1). 32–39. 25 indexed citations
14.
Ha, Eun Young, et al.. (2011). Towards a Computational Model of Narrative Visualization. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 7(2). 2–9. 4 indexed citations
15.
Boyer, Kristy Elizabeth, et al.. (2011). Investigating the Relationship Between Dialogue Structure and Tutoring Effectiveness: A Hidden Markov Modeling Approach. International Journal of Artificial Intelligence in Education. 21(1-2). 65–81. 38 indexed citations
16.
Ha, Eun Young, et al.. (2010). Exploring the Effectiveness of Lexical Ontologies for Modeling Temporal Relations with Markov Logic. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 75–78. 1 indexed citations
17.
Boyer, Kristy Elizabeth, Eun Young Ha, Robert Phillips, et al.. (2010). Dialogue Act Modeling in a Complex Task-Oriented Domain. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 297–305. 24 indexed citations
18.
Ha, Eun Young, et al.. (2010). Exploring Individual Differences in Student Writing with a Narrative Composition Support Environment. North American Chapter of the Association for Computational Linguistics. 56–64. 5 indexed citations
19.
Boyer, Kristy Elizabeth, Rob Phillips, Eun Young Ha, et al.. (2010). Leveraging Hidden Dialogue State to Select Tutorial Moves. 66–73. 8 indexed citations
20.
Ha, Eun Young, et al.. (2010). NCSU: Modeling Temporal Relations with Markov Logic and Lexical Ontology. 341–344. 23 indexed citations

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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