Jong–Hoon Oh

1.5k citations

69 papers · 962 indexed · h-index 19

Impact in

Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Neural Networks and Applications
- Semantic Web and Ontologies
Communication top 10%

Papers in ⓘ

Artificial Intelligence 59
- Natural Language Processing Techniques 43
- Topic Modeling 39
- Neural Networks and Applications 12
- Advanced Text Analysis Techniques 8
- Semantic Web and Ontologies 6
Computer Vision and Pattern Recognition 18
- Multimodal Machine Learning Applications 8
- Handwritten Text Recognition Techniques 6

Co-authors: Kentaro Torisawa (28 shared papers)Chikara Hashimoto (16 shared papers)Julien Kloetzer (16 shared papers)Key‐Sun Choi (13 shared papers)Stijn De Saeger (8 shared papers)Hitoshi Isahara (6 shared papers)Ryu Iida (9 shared papers)Kiyonori Ohtake (4 shared papers)
Journals: Language Resources and Evaluation (1 paper)Neuroreport (1 paper)Frontiers in Oncology (1 paper)Terminology International Journal of Theoretical and Applied Issues in Specialized Communication (1 paper)Information Processing & Management (1 paper)
Partner nations: Japan South Korea Hungary

In The Last Decade

Jong–Hoon Oh

64 papers receiving 878 citations

Peers

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-authors

The 25 scholars most cited alongside Jong–Hoon Oh, 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 Jong–Hoon Oh Line = papers co-authored together Jong–Hoon Oh links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Toward Future Scenario Generation: Extracting Event Causality Exploiting Semantic Relation, Context, and Association Features Chikara Hashimoto, Kentaro Torisawa, Julien Kloetzer, Motoki Sano, István Varga, Jong–Hoon Oh, Yutaka Kidawara	2014	74
2	Aid is Out There: Looking for Help from Tweets during a Large Scale Disaster Meeting of the Association for Computational Linguistics ·István Varga, Motoki Sano, Kentaro Torisawa, Chikara Hashimoto, Kiyonori Ohtake, Takao Kawai, Jong–Hoon Oh, Stijn De Saeger	2013	63
3	An English-Korean transliteration model using pronunciation and contextual rules Jong–Hoon Oh, Key‐Sun Choi	2002	62
4	Why-Question Answering using Intra- and Inter-Sentential Causal Relations Meeting of the Association for Computational Linguistics ·Jong–Hoon Oh, Kentaro Torisawa, Chikara Hashimoto, Motoki Sano, Stijn De Saeger, Kiyonori Ohtake	2013	50
5	Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web Empirical Methods in Natural Language Processing ·Chikara Hashimoto, Kentaro Torisawa, Stijn De Saeger, Jong–Hoon Oh, Jun’ichi Kazama	2012	42
6	Improving Event Causality Recognition with Multiple Background Knowledge Sources Using Multi-Column Convolutional Neural Networks Proceedings of the AAAI Conference on Artificial Intelligence ·Canasai Kruengkrai, Kentaro Torisawa, Chikara Hashimoto, Julien Kloetzer, Jong–Hoon Oh, Masahiro Tanaka	2017	42
7	Why Question Answering using Sentiment Analysis and Word Classes Jong–Hoon Oh, Kentaro Torisawa, Chikara Hashimoto, Takuya Kawada, Stijn De Saeger, Jun’ichi Kazama, Yiou Wang	2012	35
8	Multi-Column Convolutional Neural Networks with Causality-Attention for Why-Question Answering Jong–Hoon Oh, Kentaro Torisawa, Canasai Kruengkrai, Ryu Iida, Julien Kloetzer	2017	33
9	MULTIPLE NONNEGATIVE-MATRIX FACTORIZATION OF DYNAMIC PET IMAGES Frontiers in Oncology ·Jong-Hoon Ahn, Sang‐Ki Kim, Jong–Hoon Oh, Seungjin Choi	2004	27
10	Extracting clinical terms from radiology reports with deep learning Journal of Biomedical Informatics ·Kento Sugimoto, Toshihiro Takeda, Jong–Hoon Oh, Shoya Wada, Shozo Konishi, Asuka Yamahata, Shiro Manabe, Noriyuki Tomiyama, Takashi Matsunaga, Katsuyuki Nakanishi, Yasushi Matsumura	2021	27
11	Generating Event Causality Hypotheses through Semantic Relations Proceedings of the AAAI Conference on Artificial Intelligence ·Chikara Hashimoto, Kentaro Torisawa, Julien Kloetzer, Jong–Hoon Oh	2015	27
12	A Constrained EM Algorithm for Principal Component Analysis Neural Computation ·Jong-Hoon Ahn, Jong–Hoon Oh	2003	27
13	Event Causality Recognition Exploiting Multiple Annotators’ Judgments and Background Knowledge Kazuma Kadowaki, Ryu Iida, Kentaro Torisawa, Jong–Hoon Oh, Julien Kloetzer	2019	26
14	A Semi-Supervised Learning Approach to Why-Question Answering Proceedings of the AAAI Conference on Artificial Intelligence ·Jong–Hoon Oh, Kentaro Torisawa, Chikara Hashimoto, Ryu Iida, Masahiro Tanaka, Julien Kloetzer	2016	26
15	Generalization in a two-layer neural network Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics ·Kukjin Kang, Jong–Hoon Oh, Chulan Kwon, YoungAh Park	1993	25
16	Intra-Sentential Subject Zero Anaphora Resolution using Multi-Column Convolutional Neural Network Ryu Iida, Kentaro Torisawa, Jong–Hoon Oh, Canasai Kruengkrai, Julien Kloetzer	2016	25
17	A machine transliteration model based on correspondence between graphemes and phonemes ACM Transactions on Asian Language Information Processing ·Jong–Hoon Oh, Key‐Sun Choi, Hitoshi Isahara	2006	20
18	Intra-sentential Zero Anaphora Resolution using Subject Sharing Recognition Ryu Iida, Kentaro Torisawa, Chikara Hashimoto, Jong–Hoon Oh, Julien Kloetzer	2015	19
19	Validating Transliteration Hypotheses Using the Web: Web Counts vs. Web Mining Jong–Hoon Oh, Hitoshi Isahara	2007	19
20	An ensemble of transliteration models for information retrieval Information Processing & Management ·Jong–Hoon Oh, Key‐Sun Choi	2005	18

About Jong–Hoon Oh

Jong–Hoon Oh is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Information Systems and Signal Processing, having authored 69 papers that have together received 962 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (43 papers), Topic Modeling (39 papers), Neural Networks and Applications (12 papers), Multimodal Machine Learning Applications (8 papers), Advanced Text Analysis Techniques (8 papers), Blind Source Separation Techniques (7 papers), Semantic Web and Ontologies (6 papers) and Handwritten Text Recognition Techniques (6 papers). The work is most often cited by research in Artificial Intelligence (810 citations), Communication (67 citations), Computer Vision and Pattern Recognition (183 citations), Information Systems (127 citations) and Management Science and Operations Research (68 citations). Jong–Hoon Oh has collaborated with scholars based in Japan, South Korea and Hungary. Frequent 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. Their work appears in journals such as Language Resources and Evaluation, Neuroreport, Frontiers in Oncology, Terminology International Journal of Theoretical and Applied Issues in Specialized Communication and Information Processing & Management.

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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