Neil Ireson

763 total citations
27 papers, 303 citations indexed

About

Neil Ireson is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Neil Ireson has authored 27 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 9 papers in Information Systems and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Neil Ireson's work include Web Data Mining and Analysis (5 papers), Topic Modeling (4 papers) and Context-Aware Activity Recognition Systems (4 papers). Neil Ireson is often cited by papers focused on Web Data Mining and Analysis (5 papers), Topic Modeling (4 papers) and Context-Aware Activity Recognition Systems (4 papers). Neil Ireson collaborates with scholars based in United Kingdom, Italy and United States. Neil Ireson's co-authors include Fabio Ciravegna, Vitaveska Lanfranchi, Terence C. Fogarty, Mary Elaine Califf, Nicholas Kushmerick, Dayne Freitag, Alberto Lavelli, Stuart N. Wrigley, Uta Wehn and Martin Sýkora and has published in prestigious journals such as Gait & Posture, BMJ Open and IEEE Sensors Journal.

In The Last Decade

Neil Ireson

26 papers receiving 277 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Neil Ireson United Kingdom 9 118 80 51 46 31 27 303
Laura Spinsanti Italy 9 56 0.5× 26 0.3× 56 1.1× 21 0.5× 23 0.7× 15 423
Elfadil A. Mohamed United Arab Emirates 13 82 0.7× 80 1.0× 10 0.2× 26 0.6× 41 1.3× 27 388
Chenghong Zhang China 9 82 0.7× 87 1.1× 54 1.1× 10 0.2× 13 0.4× 40 345
Marco Fisichella Germany 11 179 1.5× 54 0.7× 29 0.6× 15 0.3× 25 0.8× 44 313
Teresa Onorati Spain 10 96 0.8× 74 0.9× 39 0.8× 19 0.4× 21 0.7× 33 342
Gerhard Wickler United Kingdom 8 124 1.1× 65 0.8× 46 0.9× 21 0.5× 62 2.0× 31 351
Carmen Vaca Ecuador 9 98 0.8× 67 0.8× 51 1.0× 49 1.1× 14 0.5× 41 292
Paulo J. L. Adeodato Brazil 10 196 1.7× 32 0.4× 34 0.7× 8 0.2× 9 0.3× 48 363
Mansooreh Karami United States 6 235 2.0× 105 1.3× 31 0.6× 20 0.4× 15 0.5× 8 424
Dongbo Wang China 11 85 0.7× 62 0.8× 14 0.3× 27 0.6× 7 0.2× 50 336

Countries citing papers authored by Neil Ireson

Since Specialization
Citations

This map shows the geographic impact of Neil Ireson'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 Neil Ireson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neil Ireson more than expected).

Fields of papers citing papers by Neil Ireson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Neil Ireson. 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 Neil Ireson. The network helps show where Neil Ireson may publish in the future.

Co-authorship network of co-authors of Neil Ireson

This figure shows the co-authorship network connecting the top 25 collaborators of Neil Ireson. A scholar is included among the top collaborators of Neil Ireson 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 Neil Ireson. Neil Ireson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cereatti, Andrea, Stefano Bertuletti, Tecla Bonci, et al.. (2024). Discriminating Between Indoor and Outdoor Environments During Daily Living Activities Using Local Magnetic Field Characteristics and Machine Learning Techniques. IEEE Sensors Journal. 25(1). 1507–1515. 1 indexed citations
2.
Ardle, Ríona Mc, Philip M. Brown, Heather L. Hunter, et al.. (2023). Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease. Frontiers in Neurology. 14. 1111260–1111260. 22 indexed citations
3.
4.
Bertuletti, Stefano, et al.. (2022). A deep learning model to discern indoor from outdoor environments based on data recorded by a tri-axial digital magnetic sensor. Gait & Posture. 97. 5–5. 1 indexed citations
5.
Mazumdar, Suvodeep, Stuart N. Wrigley, Neil Ireson, & Fabio Ciravegna. (2018). Harnessing location-based services for effective citizen observatories. 13. 101–108. 2 indexed citations
6.
Bai, Lu, Neil Ireson, Suvodeep Mazumdar, & Fabio Ciravegna. (2017). Lessons learned using wi-fi and Bluetooth as means to monitor public service usage. SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University). 432–440. 6 indexed citations
7.
Mazumdar, Suvodeep, Vitaveska Lanfranchi, Neil Ireson, et al.. (2016). Citizens observatories for effective Earth observations: the WeSenseIt Approach. SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University). 8 indexed citations
8.
Lanfranchi, Vitaveska, Stuart N. Wrigley, Neil Ireson, Uta Wehn, & Fabio Ciravegna. (2014). Citizens' observatories for situation awareness in flooding. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 28 indexed citations
9.
Mazumdar, Suvodeep, Vitaveska Lanfranchi, Neil Ireson, & Fabio Ciravegna. (2014). Visual analysis of real-time social media for emergency response. SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University). 67–78. 2 indexed citations
10.
Osborne, Miles, Seán Moran, Richard McCreadie, et al.. (2014). Real-Time Detection, Tracking, and Monitoring of Automatically Discovered Events in Social Media. 37–42. 71 indexed citations
11.
Tucker, Simon, et al.. (2012). Straight to the information I need: Assessing collational interfaces for emergency response.. ISCRAM. 5 indexed citations
12.
Clough, Paul, Neil Ireson, & Jeffrey Marlow. (2009). Extending Domain-Specific Resources to Enable Semantic Access to Cultural Heritage Data. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 10(6). 7. 2 indexed citations
13.
Marlow, Jeffrey, et al.. (2009). The Multimatch Project: Multilingual/Multimedia Access To Cultural Heritage On The Web.
14.
Scherp, Ansgar, et al.. (2009). Web 2.0 and traditional knowledge management processes. 222–231. 8 indexed citations
15.
Ireson, Neil. (2009). Local community situational awareness during an emergency. Zenodo (CERN European Organization for Nuclear Research). 49–54. 18 indexed citations
16.
Lanfranchi, Vitaveska & Neil Ireson. (2009). User requirements for a collective intelligence emergency response system. 198–203. 16 indexed citations
17.
Lavelli, Alberto, Mary Elaine Califf, Fabio Ciravegna, et al.. (2008). Evaluation of machine learning-based information extraction algorithms: criticisms and recommendations. Language Resources and Evaluation. 42(4). 361–393. 15 indexed citations
18.
Iria, José, Neil Ireson, & Fabio Ciravegna. (2006). An Experimental Study on Boundary Classification Algorithms for Information Extraction using SVM. 7 indexed citations
19.
Hepple, Mark, et al.. (2004). NLP-enhanced Content Filtering Within the POESIA Project.. Language Resources and Evaluation. 2 indexed citations
20.
Gammack, John, et al.. (1992). Human-centred decision support: The IDIOMS system. AI & Society. 6(4). 345–366. 6 indexed citations

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.

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