Big Data and Cognitive Computing is a premier open-access journal published by MDPI, dedicated to advancing research in the dynamic fields of artificial intelligence, computer science, information systems, and management information systems. Since its inception in 2017, the journal has established a significant presence, reflected in its impressive categorization within the Q2 quartiles for multiple disciplines in the 2023 rankings. Situated in Switzerland, the journal provides a vital platform for researchers, professionals, and students to publish groundbreaking work and access high-quality articles, enhancing the exploration of big data applications powered by cognitive computing. With an increasing global emphasis on data-driven decision-making, Big Data and Cognitive Computing offers unrestricted access to innovative research findings, addressing both theoretical and practical aspects. The journal's contributions are integral for those looking to stay at the forefront of technological advancements and their implications across various sectors.

Quantum Machine Intelligence is a leading academic journal published by Springer Nature, focusing on the rapidly evolving intersection of quantum computing and artificial intelligence. With an impressive impact factor reflected in its prestigious ranking in various categories—Q1 in Applied Mathematics, Computational Theory and Mathematics, and Theoretical Computer Science, alongside Q2 in Artificial Intelligence and Software—this journal serves as a vital platform for disseminating innovative research from 2019 to 2024. Researchers, professionals, and students are encouraged to engage with the journal’s content, which features high-quality peer-reviewed articles that explore theoretical foundations and practical applications of quantum technologies in machine intelligence. Although the journal operates under traditional subscription models, it is committed to advancing open academic discourse and accessibility in the digital age. With Scopus rankings that place it among the top echelons of its fields, the journal is an essential resource for anyone interested in the transformative potential of quantum algorithms and AI.

Frontiers of Computer Science is a leading peer-reviewed journal dedicated to advancing the field of computer science through the publication of high-quality research articles, reviews, and theoretical discussions. Published by HIGHER EDUCATION PRESS, this journal has gained significant recognition, currently boasting a prestigious impact factor and ranking in the Q1 quartile for both Computer Science (miscellaneous) and Theoretical Computer Science categories in 2023. With a focus on the intersection of computational theory and practical applications, it serves as a vital platform for researchers, professionals, and students alike who are eager to contribute to and stay updated with groundbreaking developments. The journal’s scope encompasses a wide range of topics, reflecting the diverse nature of computer science today. Operating from Beijing, China, it emphasizes Open Access, ensuring that vital research is readily available to the global academic community. With its convergence period spanning from 2013 to 2024, Frontiers of Computer Science remains committed to fostering innovation and scholarly dialogue that drives the future of technology.

International Journal of Machine Learning and Cybernetics, published by SPRINGER HEIDELBERG, serves as a pivotal platform for scholars and practitioners in the fields of Artificial Intelligence, Computer Vision, and Software Engineering. With its impressive Q2 and Q1 rankings in esteemed categories such as Artificial Intelligence and Computer Vision and Pattern Recognition, this journal boasts a commendable reputation within the academic community, further solidified by its Scopus rankings that place it in the top percentiles of its category. This journal covers critical advancements and research trends spanning the years from 2010 to 2024, facilitating knowledge exchange that drives innovation in machine learning and cybernetics. Although it operates under a subscription model, it remains accessible for extensive readership, comprising researchers, professionals, and students eager to advance their understanding in this dynamic and rapidly evolving discipline. Stay at the forefront of technology by engaging with the latest findings and methodologies published in this influential journal, identified by its ISSN 1868-8071 and E-ISSN 1868-808X.

The Journal of Experimental & Theoretical Artificial Intelligence, published by Taylor & Francis Ltd, serves as a premier platform for researchers and professionals interested in advancing the fields of artificial intelligence, software engineering, and theoretical computer science. Established in 1989, this peer-reviewed journal features original research and comprehensive reviews that explore innovative methodologies and emerging trends within these dynamic domains. With an impact factor that reflects its relevance, the journal currently ranks in Q3 across its categories, affirming its contributions to the scholarly community. The journal's commitment to quality and rigor invites submissions that bridge experimental and theoretical frameworks, thus fostering a deeper understanding of AI's applications and implications. Researchers and students can access insightful articles that drive critical discussions and inspire future work, making this journal an essential resource for anyone looking to delve into the complexities of artificial intelligence and its surrounding disciplines.

Progress in Artificial Intelligence is a leading journal published by SpringerNature, dedicated to advancing knowledge and research in the field of artificial intelligence. With a strong emphasis on the latest developments from 2012 through 2024, this journal enjoys a prominent position, holding a Q2 ranking in the prestigious Artificial Intelligence category for 2023, as well as achieving an impressive ranking of 64 out of 350 in the Computer Science - Artificial Intelligence category on Scopus, placing it in the 81st percentile. Progress in Artificial Intelligence serves as an essential platform for researchers, professionals, and students seeking to share innovative algorithms, applications, and theoretical advancements. Although it operates under a subscription model, its commitment to disseminating high-quality research and fostering collaboration in the AI community significantly contributes to the ongoing evolution of this exciting discipline.

The Journal of Intelligent Information Systems, published by Springer since 1992, is a premier academic journal that offers a multidisciplinary platform in the fields of Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Information Systems, and Software. With an impressive impact reflected in its 2023 Q2 category rankings across multiple domains and a commendable standing in the Scopus Rankings—ranking #84 in Computer Networks and Communications and #101 in Artificial Intelligence—the journal is recognized for its contribution to advancing knowledge and innovation. Although it is not an open-access journal, its accessibility through institutional subscriptions ensures that a wide range of researchers, professionals, and students can engage with high-quality, peer-reviewed research that addresses the latest advancements and trends in intelligent systems. For over three decades, this journal has effectively bridged gaps between academia and industry, making it a vital resource for those aiming to push boundaries in intelligent information systems.

MACHINE LEARNING is a premier academic journal published by SPRINGER, dedicated to advancing the field of artificial intelligence and software engineering. Established in 1986, this journal has consistently showcased pioneering research and innovative methodologies that facilitate the understanding and application of machine learning techniques across various domains. With an impressive impact factor reflecting its high-quality publications, it is classified within the top quartile (Q1) in both Artificial Intelligence and Software categories as of 2023, underscoring its critical role in these fields. The journal boasts significant Scopus rankings, placing it at the 45th and 54th positions, respectively, in Computer Science - Software and Computer Science - Artificial Intelligence, further validating its stature as a vital resource for researchers, professionals, and students alike. While not an open-access journal, MACHINE LEARNING ensures that its comprehensive peer-reviewed articles are widely circulated, fostering academic dialogue and innovation. The journal continues to be a go-to platform for cutting-edge research, providing invaluable insights and contributions that drive the future of machine learning.

Applied Computing Review is a prominent academic journal published by the Association for Computing Machinery (ACM), an esteemed organization known for advancing the computing profession. Focusing on the intersection of practical applications and theoretical foundations, this journal serves as a vital platform for disseminating research in the field of applied computing, facilitating knowledge sharing among researchers, professionals, and students alike. With an ISSN of 1559-6915, the journal encompasses a wide array of topics including software engineering, data analytics, and application development, addressing current trends and challenges in the industry. Although it does not offer open access, its rigorous peer-review process ensures high-quality publications that significantly contribute to the discipline. Positioned within a competitive landscape, Applied Computing Review is dedicated to fostering innovation and providing insightful perspectives that inspire further research, thereby solidifying its importance in the field of applied computing.

ACM Transactions on Knowledge Discovery from Data (TKDD), published by the Association for Computing Machinery, is a prestigious journal at the forefront of the interdisciplinary realm of data mining and knowledge discovery. With an impressive Q1 ranking in Computer Science and a Scopus rank of #43 out of 232, this journal stands out as a top-tier resource for innovative research that addresses complex challenges in data science. Covering impactful studies from 2007 to 2024, TKDD presents cutting-edge algorithms, methodologies, and applications that shape the future of knowledge extraction from vast datasets. While not an open-access journal, it provides a platform for researchers, professionals, and students to disseminate their findings and engage with the latest advancements in this rapidly evolving field. By fostering collaboration and knowledge sharing, TKDD plays a vital role in advancing the understanding and application of data analysis techniques, making it an essential read for anyone involved in the pursuit of knowledge from data.