About this Research Topic
We are pleased to announce the special research topic on data science as part of the Machine Learning and Artificial Intelligence journal specialty, within Frontiers in Big Data and Frontiers in Artificial Intelligence. The Research Topic is an extended collection that includes the best papers presented at the Third Joint International Conference on Data Science & Management of Data (CoDS-COMAD). The topics of interest for this special topic include, but are not limited to:
Databases: Transaction processing, query processing, query optimisation, indexing and storage, distributed data platforms, RDBMS, NoSQL systems, key-value stores, big data systems, data cleansing, data analytics, data integration, benchmarking, tuning and testing.
Data Science: Classification and regression, parallel and distributed learning, semi- and unsupervised learning, matrix and tensor methods, graph mining, network analytics, reinforcement learning, feature engineering, deep learning, Bayesian methods, time series analysis, optimization, graphical models, relational models, text analytics and NLP, information retrieval, knowledge representation, knowledge-based systems, human-in-the-loop learning, planning and reasoning.
Applications: Social network analysis, recommender systems, online advertising, bioinformatics, computational neuroscience, systems biology, multimedia processing, crowdsourcing, education, agriculture, healthcare, robotics and autonomous systems, analytics on sensor networks and IoT, computer vision, surveillance/monitoring and anomaly detection in networked systems, urban computing, and technology for emerging markets.
We invite articles on original research on all aspects of data science and data bases, detailed case studies, engineered solutions, exciting work-in-progress or even negative results that would be interesting to the broader community.
The idea of creating this Article Collection is of the Topic Editors alone, with the collaboration of the Editors-in-Chief of the Machine Learning and Artificial Intelligence specialty section, and the administrative support of Frontiers Editorial Office. This Article Collection is in no way associated, affiliated with or sponsored or supported by any other association. No initiatives and text herein should be taken as an official statement, position, or authorization of any other association or organization.
Keywords: big data systems, data analytics, semi-supervised learning, unsupervised learning, graph mining, social network analysis, multimedia processing, reinforcement learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.