Jon Hills

1.5k total citations · 2 hit papers
6 papers, 963 citations indexed

About

Jon Hills is a scholar working on Signal Processing, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Jon Hills has authored 6 papers receiving a total of 963 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Signal Processing, 3 papers in Economics and Econometrics and 2 papers in Artificial Intelligence. Recurrent topics in Jon Hills's work include Time Series Analysis and Forecasting (5 papers), Complex Systems and Time Series Analysis (3 papers) and Music and Audio Processing (3 papers). Jon Hills is often cited by papers focused on Time Series Analysis and Forecasting (5 papers), Complex Systems and Time Series Analysis (3 papers) and Music and Audio Processing (3 papers). Jon Hills collaborates with scholars based in United Kingdom. Jon Hills's co-authors include Anthony Bagnall, Jason Lines, Aaron Bostrom, Luke M. Davis, James Mapp, Graeme Richards and Beatriz de la Iglesia and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Data Mining and Knowledge Discovery and Journal of Intelligent Information Systems.

In The Last Decade

Jon Hills

6 papers receiving 938 citations

Hit Papers

Classification of time series by shapelet transformation 2013 2026 2017 2021 2013 2015 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Classification of time series by shapelet transformation
    2013 330 citations Jon Hills, Jason Lines et al. Data Mining and Knowledge Discovery profile →
  2. Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles
    2015 277 citations Anthony Bagnall, Jason Lines et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jon Hills United Kingdom 6 808 663 221 81 64 6 963
Lexiang Ye United States 5 699 0.9× 537 0.8× 195 0.9× 95 1.2× 49 0.8× 7 875
Hoang Anh Dau United States 10 486 0.6× 437 0.7× 114 0.5× 99 1.2× 41 0.6× 12 721
Mustafa Gökçe Baydoğan Türkiye 10 472 0.6× 453 0.7× 114 0.5× 52 0.6× 75 1.2× 29 696
Nurjahan Begum United States 8 457 0.6× 401 0.6× 120 0.5× 79 1.0× 30 0.5× 8 634
Nicolas Schilling Germany 9 289 0.4× 308 0.5× 91 0.4× 39 0.5× 22 0.3× 16 494
Vit Niennattrakul Thailand 10 323 0.4× 223 0.3× 81 0.4× 71 0.9× 37 0.6× 15 480
Matthew Middlehurst United Kingdom 5 312 0.4× 271 0.4× 70 0.3× 37 0.5× 50 0.8× 9 447
Maciej Łuczak Poland 9 298 0.4× 256 0.4× 84 0.4× 32 0.4× 33 0.5× 18 445
Mohammad Shokoohi-Yekta United States 5 241 0.3× 200 0.3× 39 0.2× 51 0.6× 44 0.7× 8 378
Bixiong Xu China 4 392 0.5× 521 0.8× 31 0.1× 47 0.6× 39 0.6× 4 771

Countries citing papers authored by Jon Hills

Since Specialization
Citations

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

Fields of papers citing papers by Jon Hills

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jon Hills

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

All Works

6 of 6 papers shown
1.
Bagnall, Anthony, Jason Lines, Jon Hills, & Aaron Bostrom. (2016). Time-series classification with COTE: The collective of transformation-based ensembles. UEA Digital Repository (University of East Anglia). 46 indexed citations
2.
Bagnall, Anthony, Jason Lines, Jon Hills, & Aaron Bostrom. (2015). Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles. IEEE Transactions on Knowledge and Data Engineering. 27(9). 2522–2535. 277 indexed citations breakdown →
3.
Hills, Jon, Anthony Bagnall, Beatriz de la Iglesia, & Graeme Richards. (2013). BruteSuppression: a size reduction method for Apriori rule sets. Journal of Intelligent Information Systems. 40(3). 431–454. 8 indexed citations
4.
Hills, Jon, et al.. (2013). Classification of time series by shapelet transformation. Data Mining and Knowledge Discovery. 28(4). 851–881. 330 indexed citations breakdown →
5.
Bagnall, Anthony, Luke M. Davis, Jon Hills, & Jason Lines. (2012). Transformation Based Ensembles for Time Series Classification. 307–318. 65 indexed citations
6.
Lines, Jason, Luke M. Davis, Jon Hills, & Anthony Bagnall. (2012). A shapelet transform for time series classification. 289–297. 237 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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2026