James Large

2.5k total citations · 2 hit papers
8 papers, 1.3k citations indexed

About

James Large is a scholar working on Artificial Intelligence, Signal Processing and Economics and Econometrics. According to data from OpenAlex, James Large has authored 8 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Signal Processing and 3 papers in Economics and Econometrics. Recurrent topics in James Large's work include Anomaly Detection Techniques and Applications (4 papers), Time Series Analysis and Forecasting (4 papers) and Complex Systems and Time Series Analysis (3 papers). James Large is often cited by papers focused on Anomaly Detection Techniques and Applications (4 papers), Time Series Analysis and Forecasting (4 papers) and Complex Systems and Time Series Analysis (3 papers). James Large collaborates with scholars based in United Kingdom, France and United States. James Large's co-authors include Anthony Bagnall, Jason Lines, Aaron Bostrom, Eamonn Keogh, Matthew Middlehurst, Michael Flynn, Apostolos Pesyridis, Simon Malinowski and Romain Tavenard and has published in prestigious journals such as Data Mining and Knowledge Discovery, Intelligent Data Analysis and Aerospace.

In The Last Decade

James Large

8 papers receiving 1.3k citations

Hit Papers

align trajectories

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.

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances

2016 801 citations Anthony Bagnall, Jason Lines et al. Data Mining and Knowledge Discovery profile →
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances

2020 285 citations Michael Flynn, James Large et al. Data Mining and Knowledge Discovery profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
James Large United Kingdom	8	909	750	202	119	105	8	1.3k
Aaron Bostrom United Kingdom	6	885 1.0×	735 1.0×	193 1.0×	102 0.9×	103 1.0×	7	1.4k
Eugene Tuv United States	10	506 0.6×	637 0.8×	127 0.6×	85 0.7×	161 1.5×	23	1.2k
Thanawin Rakthanmanon United States	16	1.2k 1.3×	879 1.2×	262 1.3×	80 0.7×	230 2.2×	35	1.7k
Diego Furtado Silva Brazil	20	689 0.8×	786 1.0×	145 0.7×	88 0.7×	214 2.0×	54	1.5k
Jesin Zakaria United States	10	917 1.0×	611 0.8×	187 0.9×	62 0.5×	175 1.7×	11	1.2k
Bilson Campana United States	10	763 0.8×	493 0.7×	133 0.7×	55 0.5×	183 1.7×	15	1.1k
Jason Lines United Kingdom	12	2.0k 2.2×	1.6k 2.2×	487 2.4×	190 1.6×	201 1.9×	15	2.5k
S. Chu United States	3	428 0.5×	308 0.4×	82 0.4×	45 0.4×	114 1.1×	7	740
John Paparrizos United States	18	893 1.0×	891 1.2×	233 1.2×	28 0.2×	108 1.0×	44	1.5k
Alain Ketterlin France	6	348 0.4×	231 0.3×	91 0.5×	71 0.6×	103 1.0×	13	769

Countries citing papers authored by James Large

Since Specialization

Citations

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

Fields of papers citing papers by James Large

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Large

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Flynn, Michael, et al.. (2020). The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery. 35(2). 401–449. 285 indexed citations breakdown →

2.

Middlehurst, Matthew, James Large, & Anthony Bagnall. (2020). The Canonical Interval Forest (CIF) Classifier for Time Series Classification. UEA Digital Repository (University of East Anglia). 188–195. 62 indexed citations

3.

Large, James, Jason Lines, & Anthony Bagnall. (2019). A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates. Data Mining and Knowledge Discovery. 33(6). 1674–1709. 54 indexed citations

4.

Large, James & Apostolos Pesyridis. (2019). Investigation of Micro Gas Turbine Systems for High Speed Long Loiter Tactical Unmanned Air Systems. Aerospace. 6(5). 55–55. 27 indexed citations

5.

Large, James, Anthony Bagnall, Simon Malinowski, & Romain Tavenard. (2019). On time series classification with dictionary-based classifiers. Intelligent Data Analysis. 23(5). 1073–1089. 44 indexed citations

6.

Bagnall, Anthony, Jason Lines, Aaron Bostrom, James Large, & Eamonn Keogh. (2016). The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery. 31(3). 606–660. 801 indexed citations breakdown →

7.

Large, James. (1983). The foreign-language barrier : problems in scientific communication. 22 indexed citations

8.

Large, James. (1983). The foreign-language barrier. 12 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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