Kyong Joo Oh
- Management Science and Operations Research top 1%
- Economics and Econometrics top 5%
- Finance top 2%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Topics
- Stock Market Forecasting Methods (36 papers)Complex Systems and Time Series Analysis (16 papers)Forecasting Techniques and Applications (13 papers)
- Partner nations
- South KoreaUnited States
In The Last Decade
Kyong Joo Oh
64 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 114
- Management Science and Operations Research 563
- Economics and Econometrics 346
- Finance 256
- Artificial Intelligence 207
- Electrical and Electronic Engineering 171
Countries citing papers authored by Kyong Joo Oh
This map shows the geographic impact of Kyong Joo 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 Kyong Joo Oh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyong Joo Oh more than expected).
Fields of papers citing papers by Kyong Joo Oh
This network shows the impact of papers produced by Kyong Joo 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 Kyong Joo Oh. The network helps show where Kyong Joo Oh may publish in the future.
Co-authorship network of co-authors of Kyong Joo Oh
This figure shows the co-authorship network connecting the top 25 collaborators of Kyong Joo Oh. A scholar is included among the top collaborators of Kyong Joo 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 Kyong Joo Oh. Kyong Joo Oh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | Forecasting the KOSPI 200 Stock Index Based on LSTM Autoencoder | 1 |
| 5 | 48 | |
| 6 | 17 | |
| 7 | 4 | |
| 8 | 24 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | Finding the optimal frequency for trade and development of system trading strategies in futures market using dynamic time warping | 1 |
| 12 | 70 | |
| 13 | Using factor analysis to develop verification process of IT emerging technologies | 1 |
| 14 | 13 | |
| 15 | 2 | |
| 16 | 10 | |
| 17 | 2 | |
| 18 | Using Support Vector Machine to Development Early Warning System for Financial Crisis | 2 |
| 19 | 76 | |
| 20 | A Cluster-indexing CBR Model for Collaborative Filtering Recommendation | 1 |
About Kyong Joo Oh
Kyong Joo Oh is a scholar working on Management Science and Operations Research, Finance and Signal Processing, having authored 71 papers that have together received 1.2k indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (36 papers), Complex Systems and Time Series Analysis (16 papers) and Forecasting Techniques and Applications (13 papers). The work is most often cited by research in Management Science and Operations Research (563 citations), Finance (256 citations) and Economics and Econometrics (346 citations). Kyong Joo Oh has collaborated with scholars based in South Korea and United States. Frequent co-authors include Tae Yoon Kim, Jae Joon Ahn, Chiho Kim, Dong Ha Kim, Wanki Kim, Hee Soo Lee, Sangjae Lee, Young‐Min Kim, Suk Jun Lee and Sung-Hwan Min. Their work appears in journals such as Expert Systems with Applications, Technological Forecasting and Social Change and Sustainability.
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.