Collection

Special Issue: AI + Informetrics

Submission status
Closed
Driven by the big data boom, informetrics, known as the study of quantitative aspects of information, has gained great benefits from artificial intelligence – including a wide range of intelligent agents through techniques such as neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes network, planning and language understanding. With its capacities in analyzing unstructured scalable data and streams, understanding uncertain semantics, and developing robust and repeatable models, “Artificial Intelligence + Informetrics (AII)” has demonstrated enormous success in turning big data into big value and impact by handling diverse challenges raised from multiple disciplines and research areas. For example, bibliometric-enhanced information retrieval, science mapping with topic models, streaming data analytics for tracking technological change, and entity extraction with unsupervised machine learning techniques. Such endeavors with broadened perspectives from machine intelligence would portend far-reaching implications for science, but how to effectively cohere the power of AI and informetrics to create cross-disciplinary solutions is still elusive from neither theoretical nor practical perspectives. This special issue is originally for the accepted submissions of the AII2021 Workshop, but is to call for researchers and practical users for publishing studies in line with AI+Informetrics, including constructing fundamental theories, developing novel methodologies, bridging conceptual knowledge with practical uses, and creating real-word solutions. Specific examples of fields of interest include: • Informetrics with machine learning (including deep learning) • Informetrics with natural language processing or computational linguistics • Informetrics with computer vision • Informetrics with other related AI techniques (e.g., information retrieval) • AI for science of science • AI for science, technology, & innovation • AI for research policy and strategic management • Applications of AI-enhanced informetrics

Editors

  • Yi Zhang Yi Zhang , 

    Yi Zhang

    Yi Zhang, Australian Artificial Intelligence Institute, University of Technology Sydney, Australia

  • Chengzhi Zhang Chengzhi Zhang , 

    Chengzhi Zhang

    Chengzhi Zhang, Department of Information Management, Nanjing University of Science and Technology, China

  • Philipp Mayr Philipp Mayr  &

    Philipp Mayr

    Philipp Mayr, Department Knowledge Technologies for the Social Sciences (WTS), GESIS - Leibniz-Institute for the Social Sciences, Germany

  • Arho Suominen Arho Suominen

    Arho Suominen

    Arho Suominen, VTT Technical Research Centre of Finland & Tampere University, Finland

Articles (12 in this collection)