Progress in Artificial Intelligence

6.5k citations
340 papers · indexed · active since 1950

Impact in

    • Imbalanced Data Classification Techniques
    • Anomaly Detection Techniques and Applications
    • Machine Learning and Data Classification
    • Data Stream Mining Techniques
    • Text and Document Classification Technologies
    • Metaheuristic Optimization Algorithms Research

Papers in

    • Machine Learning and Data Classification 31
    • Imbalanced Data Classification Techniques 29
    • Metaheuristic Optimization Algorithms Research 27
    • Data Stream Mining Techniques 19
    • Topic Modeling 18
    • Text and Document Classification Technologies 17
    • Anomaly Detection Techniques and Applications 16
    • Data Management and Algorithms 15

Progress in Artificial Intelligence

299 papers receiving 6.2k citations

Peers

Progress in Artificial Intelligence
Comparison fields: 5 of 211
  • Artificial Intelligence 3.3k
  • Health Information Management 215
  • Management Science and Operations Research 514
  • Computer Vision and Pattern Recognition 824
  • Industrial and Manufacturing Engineering 377
Replace Annals of Data Science with:
Annals of Data Science India
Applied Computing and Informatics India
Big Data Research China
Applied Computational Intelligence and Soft Computing India
Statistical Analysis and Data Mining The ASA Data Science Journal United States
CAAI Transactions on Intelligence Technology China
Big Data Mining and Analytics China
ACM Transactions on Management Information Systems United States
Big Data United States
International Journal on Semantic Web and Information Systems China
Progress in Artificial Intelligence relative to Annals of Data Science India Annals of Data Science's profile →
Citations per field
00.5×1.5×2.5×
Annals of Data Science · 1×
Citations per year

Countries where authors publish in Progress in Artificial Intelligence

Since Specialization
Citations

This map shows the geographic impact of research published in Progress in Artificial Intelligence. 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 papers published in Progress in Artificial Intelligence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Progress in Artificial Intelligence more than expected).

Fields of papers published in Progress in Artificial Intelligence

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Progress in Artificial Intelligence. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Progress in Artificial Intelligence.

About Progress in Artificial Intelligence

The 340 papers published in Progress in Artificial Intelligence in the last decades have received a total of 6.5k indexed citations . Papers published in Progress in Artificial Intelligence usually cover Artificial Intelligence (208 papers), Signal Processing (35 papers), Management Science and Operations Research (37 papers), Computer Vision and Pattern Recognition (55 papers) and Information Systems (43 papers) specifically the topics of Machine Learning and Data Classification (31 papers), Imbalanced Data Classification Techniques (29 papers), Metaheuristic Optimization Algorithms Research (27 papers), Data Stream Mining Techniques (19 papers), Topic Modeling (18 papers), Text and Document Classification Technologies (17 papers), Anomaly Detection Techniques and Applications (16 papers) and Data Management and Algorithms (15 papers). The most active scholars publishing in Progress in Artificial Intelligence are Bartosz Krawczyk, Anamika Dhillon, Gyanendra K. Verma, João Gama, Hadi Fanaee‐T, Nitesh V. Chawla, Amparo Alonso‐Betanzos, T. Ryan Hoens, Robi Polikar and Verónica Bolón‐Canedo.

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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