Jong–Hoon Oh

1.5k total citations
69 papers, 962 citations indexed

About

Jong–Hoon Oh is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Jong–Hoon Oh has authored 69 papers receiving a total of 962 indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 9 papers in Statistical and Nonlinear Physics. Recurrent topics in Jong–Hoon Oh's work include Natural Language Processing Techniques (43 papers), Topic Modeling (39 papers) and Neural Networks and Applications (12 papers). Jong–Hoon Oh is often cited by papers focused on Natural Language Processing Techniques (43 papers), Topic Modeling (39 papers) and Neural Networks and Applications (12 papers). Jong–Hoon Oh collaborates with scholars based in Japan, South Korea and Hungary. Jong–Hoon Oh's co-authors include Kentaro Torisawa, Chikara Hashimoto, Julien Kloetzer, Key‐Sun Choi, Stijn De Saeger, Hitoshi Isahara, Ryu Iida, Kiyonori Ohtake, Canasai Kruengkrai and István Varga and has published in prestigious journals such as Neuroreport, Neural Computation and Neurocomputing.

In The Last Decade

Jong–Hoon Oh

64 papers receiving 878 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jong–Hoon Oh Japan 19 810 183 127 68 67 69 962
Zornitsa Kozareva United States 17 1.3k 1.6× 155 0.8× 225 1.8× 99 1.5× 42 0.6× 55 1.4k
Josiane Mothe France 15 492 0.6× 132 0.7× 268 2.1× 52 0.8× 38 0.6× 103 792
Kentaro Torisawa Japan 25 1.6k 1.9× 190 1.0× 269 2.1× 113 1.7× 147 2.2× 103 1.7k
Aria Haghighi United States 21 1.8k 2.2× 154 0.8× 236 1.9× 105 1.5× 34 0.5× 34 1.9k
Steffen Eger Germany 14 816 1.0× 142 0.8× 125 1.0× 28 0.4× 23 0.3× 74 993
Hiroya Takamura Japan 17 1.1k 1.4× 135 0.7× 175 1.4× 47 0.7× 17 0.3× 131 1.2k
Jurgen Van Gael United Kingdom 13 486 0.6× 100 0.5× 150 1.2× 56 0.8× 20 0.3× 20 803
Maya Ramanath Germany 14 634 0.8× 129 0.7× 275 2.2× 115 1.7× 36 0.5× 53 871
Lev Ratinov United States 8 1.3k 1.6× 131 0.7× 182 1.4× 152 2.2× 36 0.5× 11 1.4k
Deepak Ravichandran United States 14 1.6k 2.0× 235 1.3× 569 4.5× 86 1.3× 41 0.6× 22 1.9k

Countries citing papers authored by Jong–Hoon Oh

Since Specialization
Citations

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

Fields of papers citing papers by Jong–Hoon Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jong–Hoon Oh. 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 Jong–Hoon Oh. The network helps show where Jong–Hoon Oh may publish in the future.

Co-authorship network of co-authors of Jong–Hoon Oh

This figure shows the co-authorship network connecting the top 25 collaborators of Jong–Hoon Oh. A scholar is included among the top collaborators of Jong–Hoon Oh 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 Jong–Hoon Oh. Jong–Hoon Oh 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.
Oh, Jong–Hoon, et al.. (2019). Open-Domain Why-Question Answering with Adversarial Learning to Encode Answer Texts. 4227–4237. 5 indexed citations
2.
Tanaka, Masahiro, Kiyonori Ohtake, Jong–Hoon Oh, et al.. (2016). WISDOM X, DISAANA and D-SUMM: Large-scale NLP Systems for Analyzing Textual Big Data.. International Conference on Computational Linguistics. 263–267. 17 indexed citations
3.
Torisawa, Kentaro, et al.. (2014). Million-scale Derivation of Semantic Relations from a Manually Constructed Predicate Taxonomy. International Conference on Computational Linguistics. 1423–1434. 4 indexed citations
4.
Varga, István, Kentaro Torisawa, Chikara Hashimoto, et al.. (2013). Aid is Out There: Looking for Help from Tweets during a Large Scale Disaster. Meeting of the Association for Computational Linguistics. 1619–1629. 63 indexed citations
5.
Oh, Jong–Hoon, et al.. (2013). Why-Question Answering using Intra- and Inter-Sentential Causal Relations. Meeting of the Association for Computational Linguistics. 1733–1743. 50 indexed citations
6.
Hashimoto, Chikara, Kentaro Torisawa, Stijn De Saeger, Jong–Hoon Oh, & Jun’ichi Kazama. (2012). Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web. Empirical Methods in Natural Language Processing. 619–630. 42 indexed citations
7.
Yamada, Ichiro, et al.. (2012). Generating Information-Rich Taxonomy Using Wikipedia. Journal of Natural Language Processing. 19(1). 3–23. 1 indexed citations
8.
Yamada, Ichiro, Jong–Hoon Oh, Chikara Hashimoto, et al.. (2011). Extending WordNet with Hypernyms and Siblings Acquired from Wikipedia. International Joint Conference on Natural Language Processing. 874–882. 7 indexed citations
9.
Oh, Jong–Hoon, Ichiro Yamada, Kentaro Torisawa, & Stijn De Saeger. (2010). Co-STAR: A Co-training Style Algorithm for Hyponymy Relation Acquisition from Structured and Unstructured Text. International Conference on Computational Linguistics. 842–850. 2 indexed citations
10.
Oh, Jong–Hoon & Hitoshi Isahara. (2008). Hypothesis Selection in Machine Transliteration: A Web Mining Approach. International Joint Conference on Natural Language Processing. 233–240. 4 indexed citations
11.
Murata, Masaki, Jong–Hoon Oh, Qing Ma, & Hitoshi Isahara. (2007). Applying Multiple Characteristics and Techniques in the NICT Information Retrieval System at NTCIR-6. NTCIR.
12.
Oh, Jong–Hoon & Key‐Sun Choi. (2005). Automatic Extraction of English-Korean Translations for Constituents of Technical Terms. International Joint Conference on Natural Language Processing. 2 indexed citations
13.
Oh, Jong–Hoon, et al.. (2002). Adaptive Predistortion Filter for Linearization of Digital PWM Power Amplifier using Neural Networks. Journal of the Audio Engineering Society. 3 indexed citations
14.
Oh, Jong–Hoon, et al.. (2002). Word Sense Disambiguation with Information Retrieval Technique.. Language Resources and Evaluation. 1 indexed citations
15.
Oh, Jong–Hoon, Kyung‐Soon Lee, & Key‐Sun Choi. (2002). Automatic Term Recognition using Domain Similarity and Statistical Methods. Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong. 29(4). 258–269.
16.
Oh, Jong–Hoon, et al.. (2001). TREC-10 Experiments at KAIST: Batch Filtering and Question Answering. Text REtrieval Conference. 9 indexed citations
17.
Lee, Kyung‐Soon, et al.. (2000). TREC-9 Experiments at KAIST: QA, CLIR and Batch Filtering.. Text REtrieval Conference. 5 indexed citations
18.
Oh, Jong–Hoon & H. Sebastian Seung. (1997). Learning Generative Models with the Up Propagation Algorithm. neural information processing systems. 10. 605–611. 8 indexed citations
19.
Oh, Jong–Hoon, et al.. (1996). Statistical Mechanics of the Mixture of Experts. Neural Information Processing Systems. 9. 183–189. 7 indexed citations
20.
Oh, Jong–Hoon, Chulan Kwon, & Sungzoon Cho. (1995). Neural networks : the statistical mechanics perspective : proceedings of the CTP-PBSRI Joint Workshop on Theoretical Physics, POSTECH, Pohang, Korea, 2-4 February 95. WORLD SCIENTIFIC eBooks. 5 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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