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Nhóm Nghiên cứu trắc lượng thông tin (INFORMETRICS)

Introduction

Introduction

Introduction

Informetrics Research Group (INFORMETRICS) was established on 29/07/2016 for studies regarding research policies in universities, especially in the scientific research and university-ranking aspects. IRG has developed and investigated new tools to evaluate the research performance of individuals, institutions, countries, regions, and the world with different aspects of the research performance. The outcomes then provide key information to policymakers and all people paying their attention to research and development.

Mission and vision

  • Build a center of excellence of international standing in the conduct and translation of research into scientific activities and higher education;
  • Conduct high-quality research in scientific studies;
  • Foster talents in informetrics research;
  • Disseminate research findings in international journals;
  • Provide leadership in identifying emerging issues in scientific research in Vietnam.

Research Topics

Research Topics

  • Scientometrics regarding quantitative aspects of science, especially in education, social sciences, and humanities, economics;
  • Webometrics and Cybermetric for quantitative aspects of the World Wide Web and/or including electronic resources;
  • Bibliometrics for quantitative aspects of recorded information.

Current Members

Current Members

Full-time researcher of Informetrics Research Group

H-Index (WoS): 18; Citation (WoS): > 813

H-Index (Scopus): 19; Citation (Scopus): > 942


Publications

Publications

    2022

    1. Ham, Nguyen; Le, Tuong, A Fast Algorithm for Mining Top-Rank-k Erasable Closed Patterns, Computers, Materials, and Continua, 72(2): 3571-3583., 2022 (ISI)
    2. Ham Nguyen, Nguyen Le, Huong Bui, Tuong Le, A new approach for efficiently mining frequent weighted utility patterns, Applied Intelligence, 2022 (ISI)
    3. Ham Nguyen, Tuong Le, Minh Nguyen, Philippe Fournier-Viger, Vincent S. Tseng, Bay Vo, Mining frequent weighted utility itemsets in hierarchical quantitative databases, Knowledge-Based Systems, 237: 107709, 2022 (ISI)

    2021

    1. Bay Vo, Huy-Cuong Nguyen, Bao Huynh, Tuong Le, Efficient Methods for Clickstream Pattern Mining on Incremental Databases, IEEE Access, 9: 161305-161317, 2021 (ISI)