Alberto Cano

3.8k total citations
93 papers, 2.6k citations indexed

About

Alberto Cano is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Alberto Cano has authored 93 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Artificial Intelligence, 17 papers in Information Systems and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Alberto Cano's work include Machine Learning and Data Classification (27 papers), Data Stream Mining Techniques (25 papers) and Text and Document Classification Technologies (15 papers). Alberto Cano is often cited by papers focused on Machine Learning and Data Classification (27 papers), Data Stream Mining Techniques (25 papers) and Text and Document Classification Technologies (15 papers). Alberto Cano collaborates with scholars based in United States, Spain and Norway. Alberto Cano's co-authors include Sebastián Ventura, Bartosz Krawczyk, Youcef Djenouri, Asma Belhadi, Jerry Chun‐Wei Lin, Amelia Zafra, Cristóbal Romero, Djamel Djenouri, Joaquín Bautista Valhondo and José María Luna and has published in prestigious journals such as European Journal of Operational Research, Expert Systems with Applications and IEEE Access.

In The Last Decade

Alberto Cano

85 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alberto Cano United States 30 1.7k 448 362 357 326 93 2.6k
Kalyan Veeramachaneni United States 21 1.3k 0.7× 363 0.8× 135 0.4× 365 1.0× 471 1.4× 82 2.5k
Fei Hao China 26 853 0.5× 534 1.2× 139 0.4× 258 0.7× 464 1.4× 167 2.2k
Una-May O’Reilly United States 26 1.6k 0.9× 382 0.9× 101 0.3× 226 0.6× 558 1.7× 147 3.0k
Ge Yu China 30 1.6k 0.9× 721 1.6× 158 0.4× 636 1.8× 1.1k 3.3× 380 3.8k
Jianye Hao China 27 1.0k 0.6× 317 0.7× 85 0.2× 218 0.6× 382 1.2× 184 2.7k
Gongqing Wu China 13 1.1k 0.6× 753 1.7× 60 0.2× 287 0.8× 384 1.2× 55 2.2k
Zhenjie Zhang China 26 1.1k 0.7× 565 1.3× 203 0.6× 191 0.5× 695 2.1× 100 2.2k
Elena Baralis Italy 25 1.1k 0.7× 866 1.9× 73 0.2× 196 0.5× 676 2.1× 193 2.3k
Runhe Huang Japan 19 553 0.3× 438 1.0× 504 1.4× 347 1.0× 647 2.0× 149 2.0k
Lichao Sun United States 28 2.3k 1.3× 727 1.6× 169 0.5× 360 1.0× 727 2.2× 99 3.6k

Countries citing papers authored by Alberto Cano

Since Specialization
Citations

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

Fields of papers citing papers by Alberto Cano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alberto Cano

This figure shows the co-authorship network connecting the top 25 collaborators of Alberto Cano. A scholar is included among the top collaborators of Alberto Cano 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 Alberto Cano. Alberto Cano 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.
2.
Cano, Alberto, et al.. (2024). A comprehensive analysis of concept drift locality in data streams. Knowledge-Based Systems. 289. 111535–111535. 9 indexed citations
3.
Krawczyk, Bartosz, et al.. (2023). A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework. Machine Learning. 113(7). 4165–4243. 76 indexed citations
4.
Džeroski, Sašo, et al.. (2023). Aging and rejuvenating strategies for fading windows in multi-label classification on data streams. Research Commons (University of Waikato). 390–397. 4 indexed citations
5.
6.
Cano, Alberto, et al.. (2023). Dynamic budget allocation for sparsely labeled drifting data streams. Information Sciences. 654. 119821–119821. 3 indexed citations
7.
Zarpel�ão, Bruno Bogaz, et al.. (2021). Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction. Sensors. 21(21). 7333–7333. 21 indexed citations
8.
Belhadi, Asma, Youcef Djenouri, Gautam Srivastava, Alberto Cano, & Jerry Chun‐Wei Lin. (2021). Hybrid Group Anomaly Detection for Sequence Data: Application to Trajectory Data Analytics. IEEE Transactions on Intelligent Transportation Systems. 23(7). 9346–9357. 34 indexed citations
9.
Belhadi, Asma, Youcef Djenouri, Jerry Chun‐Wei Lin, Chongsheng Zhang, & Alberto Cano. (2020). Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem. IEEE Access. 8. 10569–10583. 31 indexed citations
10.
Nguyen, Hung T., Alberto Cano, Tam Vu, & Thang N. Dinh. (2019). Blocking Self-Avoiding Walks Stops Cyber-Epidemics: A Scalable GPU-Based Approach. IEEE Transactions on Knowledge and Data Engineering. 32(7). 1263–1275. 14 indexed citations
11.
Cano, Alberto & John D. Leonard. (2019). Interpretable Multiview Early Warning System Adapted to Underrepresented Student Populations. IEEE Transactions on Learning Technologies. 12(2). 198–211. 58 indexed citations
12.
Djenouri, Youcef, Asma Belhadi, Jerry Chun‐Wei Lin, & Alberto Cano. (2019). Adapted K-Nearest Neighbors for Detecting Anomalies on Spatio–Temporal Traffic Flow. IEEE Access. 7. 10015–10027. 85 indexed citations
13.
Djenouri, Youcef, Asma Belhadi, Jerry Chun‐Wei Lin, Djamel Djenouri, & Alberto Cano. (2019). A Survey on Urban Traffic Anomalies Detection Algorithms. IEEE Access. 7. 12192–12205. 97 indexed citations
14.
Ventura, Sebastián, et al.. (2019). Distributed Selection of Continuous Features in Multilabel Classification Using Mutual Information. IEEE Transactions on Neural Networks and Learning Systems. 31(7). 1–14. 50 indexed citations
15.
Kecman, Vojislav, et al.. (2018). OLLAWV: OnLine Learning Algorithm using Worst-Violators. Applied Soft Computing. 66. 384–393. 13 indexed citations
16.
Ventura, Sebastián, et al.. (2018). Distributed nearest neighbor classification for large-scale multi-label data on spark. Future Generation Computer Systems. 87. 66–82. 33 indexed citations
17.
Cano, Alberto, et al.. (2018). Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams. 23–37. 9 indexed citations
18.
Cano, Alberto & Ángela Rojas. (2016). Autómatas celulares y aplicaciones. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 33–48. 2 indexed citations
19.
Cano, Alberto, José María Luna, Eva Gibaja, & Sebastián Ventura. (2015). LAIM discretization for multi-label data. Information Sciences. 330. 370–384. 34 indexed citations
20.
Cano, Alberto, et al.. (2015). Early dropout prediction using data mining: a case study with high school students. Expert Systems. 33(1). 107–124. 200 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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