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Researcher · Manchester Metropolitan University · United Kingdom

Matthew Shardlow

Matthew Shardlow publishes mostly in Artificial Intelligence, Information Systems and Molecular Biology, on topics such as Text Readability and Simplification, Natural Language Processing Techniques and Topic Modeling.

ORCID 0000-0003-1129-2750 OpenAlex
World rank
#763,937
of 7,710,434 ranked researchers
Rank in United Kingdom
#63,775
of 367,258
Works
98
Citations
1.8k
Citations per work
18.6
h-index
21
i10-index 31Top 12% in Artificial Intelligence
Matthew Shardlow

What does Matthew Shardlow research?

Matthew Shardlow's work is mostly in Computer Science (77%), Biochemistry, Genetics and Molecular Biology (3%), Health Professions (3%).

Physical Sciences: 75 works · 76.8% of their workComputer Science: 75 works · 76.8% of their workArtificial Intelligence: 71 works · 72.5% of their workInformation Systems: 4 works · 4.3% of their workEverything else: 13 works · 13.4% of their workHealth Sciences: 5 works · 5.1% of their workHealth Professions: 3 works · 3.0% of their workGeneral Health Professions: 3 works · 3.0% of their workMedicine: 2 works · 2.1% of their workPsychiatry and Mental health: 2 works · 2.1% of their workLife Sciences: 3 works · 3.4% of their workBiochemistry, Genetics and Molecular Biology: 3 works · 3.4% of their workMolecular Biology: 3 works · 3.4% of their workSocial Sciences: 1 works · 1.3% of their workSocial Sciences: 1 works · 1.3% of their workSafety Research: 1 works · 1.3% of their workTHEIR WORKMatthew Shardlow98works
Life Sciences3%Physical Sciences77%Health Sciences5%Social Sciences1%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science7576.8%
  2. Everything else1313.4%
    1. Health Professions33.0%
    2. Medicine22.1%
    1. Biochemistry, Genetics and Molecular Biology33.4%
    1. Social Sciences11.3%
  1. 1Artificial Intelligence72% of their works
  2. 2Information Systems4% of their works
  3. 3Molecular Biology3% of their works
  4. 4General Health Professions3% of their works
  5. 5Psychiatry and Mental health2% of their works
  6. 6Safety Research1% of their works

Research topics

Which keywords describe Matthew Shardlow's research?

The keywords of their largest research topics: Neural Networks, Machine Learning, Natural Language Processing, Text Classification, Readability Assessment, Text Simplification, Neural Machine Translation and Statistical Machine Translation.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.

All 21 words, with their numbers
  1. Neural Networks963 topics
  2. Machine Learning613 topics
  3. Natural Language Processing562 topics
  4. Text Classification502 topics
  5. Readability Assessment481 topic
  6. Text Simplification481 topic
  7. Neural Machine Translation461 topic
  8. Statistical Machine Translation461 topic
  9. Machine Translation441 topic
  10. Word Representation441 topic
  11. Text Mining152 topics
  12. Biomedical Literature81 topic
  13. Biomedical Ontologies81 topic
  14. Opinion Mining71 topic
  15. Sentiment Analysis71 topic
  16. Authorship Attribution61 topic
  17. Stylometry61 topic
  18. Language Barriers51 topic
  19. Medical Interpreters51 topic
  20. Automatic41 topic
  21. Extraction41 topic

Where does Matthew Shardlow work?

Matthew Shardlow's main affiliation in the publication record is Manchester Metropolitan University, United Kingdom.

How many publications and citations does Matthew Shardlow have?

OpenAlex counts 98 works and 1,818 citations for Matthew Shardlow, an h-index of 21, ranking #763,937 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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