Richard F. E. Sutcliffe
- Artificial Intelligence top 5%
- Natural Language Processing Techniques 23
- Topic Modeling 22
- Advanced Text Analysis Techniques 11
- Sentiment Analysis and Opinion Mining 9
- Semantic Web and Ontologies 6
- Text and Document Classification Technologies 5
- Computer Science Applications top 10%
- Music top 10%
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- Music and Audio Processing 7
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- Biomedical Text Mining and Ontologies 5
- Journals
- Language Resources and Evaluation (4 papers)Neurocomputing (2 papers)Applied Intelligence (2 papers)
- Partner nations
- United KingdomChinaIreland
In The Last Decade
Richard F. E. Sutcliffe
49 papers receiving 518 citations
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 390
- Computer Science Applications 35
- Music 14
- Signal Processing 43
- Experimental and Cognitive Psychology 44
Countries citing papers authored by Richard F. E. Sutcliffe
This map shows the geographic impact of Richard F. E. Sutcliffe'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 Richard F. E. Sutcliffe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard F. E. Sutcliffe more than expected).
Fields of papers citing papers by Richard F. E. Sutcliffe
This network shows the impact of papers produced by Richard F. E. Sutcliffe. 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 Richard F. E. Sutcliffe. The network helps show where Richard F. E. Sutcliffe may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Richard F. E. Sutcliffe, 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 | 2025 | 3 | |
| 2 | 2024 | 4 | |
| 3 | 2023 | 8 | |
| 4 | 2023 | 7 | |
| 5 | 2023 | 4 | |
| 6 | 2022 | 8 | |
| 7 | 2022 | 24 | |
| 8 | 2022 | 15 | |
| 9 | 2021 | 22 | |
| 10 | 2021 | 43 | |
| 11 | 2021 | 8 | |
| 12 | 2020 | 26 | |
| 13 | 2019 | 66 | |
| 14 | 2019 | 22 | |
| 15 | Capturing the Meaning of Complex Texts about Music | 2017 | 0 |
| 16 | The C@merata task at MediaEval 2016: Natural Language Queries Derived from Exam Papers, Articles and Other Sources against Classical Music Scores in MusicXML. | 2016 | 0 |
| 17 | The C@merata Task at MediaEval 2014: Natural Language Queries on Classical Music Scores | 2014 | 11 |
| 18 | Question Answering using the DLT System at TREC 2005 | 2005 | 1 |
| 19 | A Parallel English-Japanese Query Collection for the Evaluation of On-Line Help Systems | 2000 | 2 |
| 20 | Mixing binary and continuous connection schemes for knowledge access | 1986 | 7 |
About Richard F. E. Sutcliffe
Richard F. E. Sutcliffe is a scholar working on Music, Artificial Intelligence, Signal Processing, Computer Science Applications and Information Systems, having authored 54 papers that have together received 567 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (23 papers), Topic Modeling (22 papers), Advanced Text Analysis Techniques (11 papers), Sentiment Analysis and Opinion Mining (9 papers), Music and Audio Processing (7 papers), Semantic Web and Ontologies (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Text and Document Classification Technologies (5 papers). The work is most often cited by research in Artificial Intelligence (390 citations), Computer Science Applications (35 citations), Music (14 citations), Signal Processing (43 citations) and Experimental and Cognitive Psychology (44 citations). Richard F. E. Sutcliffe has collaborated with scholars based in United Kingdom, China and Ireland. Frequent co-authors include Jun Feng, Xia Sun, Pamela Forner, Anselmo Peñas, Álvaro Rodrigo, Corina Forăscu, Eduard Hovy, Ke Dong, Long Ma and Su‐Shing Chen. Their work appears in journals such as Language Resources and Evaluation, Neurocomputing, Applied Intelligence, Journal of Quantitative Linguistics and Knowledge-Based Systems.
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.