Keizo Oyama
- Information Systems top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research top 10%
- Signal Processing top 10%
- Co-authors
- Akiko AizawaKoji EguchiYi YuNoriko KandoHayato YamanaKyo KageuraXiaojun MaMasaharu Yoshioka
- Topics
- Web Data Mining and Analysis (19 papers)Information Retrieval and Search Behavior (12 papers)Semantic Web and Ontologies (7 papers)
In The Last Decade
Keizo Oyama
28 papers receiving 224 citations
Peers
Comparison fields: 5 of 43
- Information Systems 123
- Artificial Intelligence 119
- Computer Vision and Pattern Recognition 66
- Management Science and Operations Research 56
- Signal Processing 54
Countries citing papers authored by Keizo Oyama
This map shows the geographic impact of Keizo Oyama'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 Keizo Oyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keizo Oyama more than expected).
Fields of papers citing papers by Keizo Oyama
This network shows the impact of papers produced by Keizo Oyama. 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 Keizo Oyama. The network helps show where Keizo Oyama may publish in the future.
Co-authorship network of co-authors of Keizo Oyama
This figure shows the co-authorship network connecting the top 25 collaborators of Keizo Oyama. A scholar is included among the top collaborators of Keizo Oyama 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 Keizo Oyama. Keizo Oyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 2 | |
| 3 | 36 | |
| 4 | 2 | |
| 5 | 11 | |
| 6 | 4 | |
| 7 | Web Page Classification exploiting Surrounding Pages with Noisy Page Filtering. | 0 |
| 8 | 0 | |
| 9 | Building a terabyte-scale web data collection "NW1000G-04" in the NTCIR-5 WEB task | 1 |
| 10 | Overview of the NTCIR-5 WEB Navigational Retrieval Subtask 2 (Navi-2). | 8 |
| 11 | Overview of the NTCIR-4 WEB Navigational Retrieval Task 1. | 5 |
| 12 | Overview of WEB Task at the Fourth NTCIR Workshop | 3 |
| 13 | Overview of the Informational Retrieval Task at NTCIR-4 WEB. | 12 |
| 14 | 2 | |
| 15 | Evaluation Methods for Web Retrieval Tasks Considering Hyperlink Structure | 11 |
| 16 | System Evaluation Methods for Web Retrieval Tasks Considering Hyperlink Structure. | 1 |
| 17 | Overview of the Web Retrieval Task at the Third NTCIR Workshop | 21 |
| 18 | Consideration on Web Information Retrieval Challenge -A New Task of NTCIR Workshop - 3- | 1 |
| 19 | Proceedings of the International Conference on Dublin Core and Metadata Applications 2001 | 16 |
| 20 | 8 |
About Keizo Oyama
Keizo Oyama is a scholar working on Information Systems, Signal Processing and Computer Vision and Pattern Recognition, having authored 36 papers that have together received 241 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (19 papers), Information Retrieval and Search Behavior (12 papers) and Semantic Web and Ontologies (7 papers). The work is most often cited by research in Information Systems (123 citations), Signal Processing (54 citations) and Management Science and Operations Research (56 citations). Keizo Oyama has collaborated with scholars based in Japan, India and Singapore. Frequent co-authors include Akiko Aizawa, Koji Eguchi, Yi Yu, Noriko Kando, Hayato Yamana, Kyo Kageura, Xiaojun Ma, Masaharu Yoshioka, Wei Duan and Tetsuro Kobayashi. Their work appears in journals such as Neural Computing and Applications, ACM Transactions on Multimedia Computing Communications and Applications and ACM SIGIR Forum.
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.