Visualization and Mapping of Knowledge and Science Landscapes in Expert Systems With Applications Journal

A 30 Years' Bibliometric Analysis

Datos Bibliográficos

ID3304575
AutoresShaher H Zyoud (0000-0002-2832-1047, Palestine Technical University - Kadoorie, autor de correspondencia), Ahed H Zyoud, Ahed Zyoud (0000-0001-5812-5955, An-Najah National University)
Año2021
Volumen11
Número2
Fecha de publicación2021-04-01
Open AccessSí
TipoARTICLE
RevistaSAGE Open (JOURNAL)
Identificadores de la revistaISSN: 2158-2440 • E-ISSN: 2158-2440
EditorialSAGE Publications Inc (PUBLISHER)
DOI10.1177/21582440211027574
OpenAlexW3175889490
IdiomaEN
Citas recibidas3
Referencias citadas85

The Expert Systems With Applications (ESWA) is a leading journal in the fields of computer science and engineering. Motivated by its outstanding performance, this paper seeks to develop a comprehensive overview of research activities in ESWA since its inception in 1990. In this regard, bibliometric techniques have been utilized to characterize the status quo, dynamics, and development trends of research patterns in ESWA. In doing so, the work used Scopus database as a source of data required. A data visualization software, visualization of similarities (VOS) viewer, was used to map the bibliographic material. The Scopus database yielded 12,254 documents published in ESWA from 105 countries with an average of 408 documents/year. The most productive country was Taiwan (2,069 documents; 17.0%). National Cheng Kung University, Taiwan, was the most productive institution (219 documents; 1.8%). The major topics which will continue to be active include genetic algorithms, data mining, neural networks, support vector machines, classification and machine learning, feature selection, particle swarm optimization, fuzzy logic, and clustering. The outcomes underline the significant growth of ESWA through time. The vitality of topics addressed in ESWA to solve real-world problems boosts the progress and advancements of knowledge in this journal

Bibliometrics · Cluster analysis · Data mining · Data science · Information retrieval · Scopus · Status quo · Visualization · Computer Science · Imbalanced Data Classification Techniques · Online Learning and Analytics · Software Engineering Research · Artificial Intelligence

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