Sumio Fujita
- Information Systems top 5%
- Information Retrieval and Search Behavior 14
- Expert finding and Q&A systems 8
- Recommender Systems and Techniques 7
- Artificial Intelligence top 10%
- Topic Modeling 18
- Natural Language Processing Techniques 8
- Advanced Text Analysis Techniques 5
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- Data-Driven Disease Surveillance 8
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- Data Management and Algorithms 7
- Co-authors
- Tomohiro SonobeKen‐ichi KawarabayashiNaoto OhsakaTakehiro YamamotoShoko WakamiyaDaichi AmagataTakahiro HaraEiji Aramaki
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Sumio Fujita
47 papers receiving 231 citations
Peers
Comparison fields: 5 of 56
- Information Systems 118
- Artificial Intelligence 135
- Statistical and Nonlinear Physics 33
- Modeling and Simulation 12
- Computer Science Applications 10
Countries citing papers authored by Sumio Fujita
This map shows the geographic impact of Sumio Fujita'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 Sumio Fujita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumio Fujita more than expected).
Fields of papers citing papers by Sumio Fujita
This network shows the impact of papers produced by Sumio Fujita. 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 Sumio Fujita. The network helps show where Sumio Fujita may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sumio Fujita, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 2 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 4 | |
| 4 | 2022 | 2 | |
| 5 | 2022 | 5 | |
| 6 | 2021 | 9 | |
| 7 | 2021 | 3 | |
| 8 | 2021 | 2 | |
| 9 | 2021 | 3 | |
| 10 | 2020 | 3 | |
| 11 | 2020 | 2 | |
| 12 | Dual Constrained Question Embeddings with Relational Knowledge Bases for Simple Question Answering | 2017 | 1 |
| 13 | Overview of the NTCIR-12 IMine-2 Task. | 2016 | 12 |
| 14 | 2005 | 1 | |
| 15 | Revisiting Again Document Length Hypotheses TREC-2004 Genomics Track Experiments at Patolis | 2004 | 27 |
| 16 | Notes on the Limits of CLIR Effectiveness: NTCIR-2 Evaluation Experiments at Justsystem. | 2001 | 2 |
| 17 | More Reflections on "Aboutness" TREC-2001 Evaluation Experiments at Justsystem. | 2001 | 9 |
| 18 | Evaluation of Japanese phrasal indexing with a large test collection | 2000 | 4 |
| 19 | Reflections on "Aboutness" TREC-9 Evaluation Experiments at Justsystem. | 2000 | 11 |
| 20 | Notes on Phrasal Indexing: JSCB Evaluation Experiments at NTCIR AD HOC. | 1999 | 18 |
About Sumio Fujita
Sumio Fujita is a scholar working on Information Systems, Artificial Intelligence and Modeling and Simulation, having authored 53 papers that have together received 269 indexed citations. Recurring topics across this work include Topic Modeling (18 papers), Information Retrieval and Search Behavior (14 papers), Expert finding and Q&A systems (8 papers), Data-Driven Disease Surveillance (8 papers), Natural Language Processing Techniques (8 papers), Recommender Systems and Techniques (7 papers), Data Management and Algorithms (7 papers) and Advanced Text Analysis Techniques (5 papers). The work is most often cited by research in Information Systems (118 citations), Artificial Intelligence (135 citations) and Statistical and Nonlinear Physics (33 citations). Sumio Fujita has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Tomohiro Sonobe, Ken‐ichi Kawarabayashi, Naoto Ohsaka, Takehiro Yamamoto, Shoko Wakamiya, Daichi Amagata, Takahiro Hara, Eiji Aramaki, Shuntaro Yada and Nobuyuki Shimizu. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Access.
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.