Comprehensive review of academic search systems: evolution, analysis, and future research directions

  • Khalid, Shah; 
  • Almutairi, Sulaiman; 
  • Namoun, Abdallah; 
  • Khan, Jawad; 
  • Ali Khattak, Hasan; 
  • 외 1명
Citations

WEB OF SCIENCE

4
Citations

SCOPUS

7

초록

Most countries today emphasize scientific research and invest heavily in it. As a result, the number of scholarly documents has increased dramatically. Both academics and industry professionals seek to retrieve relevant papers efficiently. However, identifying relevant documents on a given topic using current academic search systems is challenging. The reasons include the exponential growth of research publications, ambiguity and limitations in searchers' keywords, and the complexity of citation networks. Over the past decades, several methods have been proposed to ease the laborious task of searching for relevant papers. Various books and review articles summarize these methodologies, findings, and implications. However, they often fail to provide a detailed retrospective of recent advances, including their evolution, current state, and challenges. This article addresses that gap by reviewing the most relevant and authoritative literature on advances in academic search systems. It proposes a generic layered architecture of scholarly retrieval systems and provides a detailed analysis of ranking methodologies, datasets, and evaluation methods. Additionally, it identifies critical open research challenges and issues, offering a promising foundation for future research and development in this vital field.

키워드

Academic search; Ranking strategies; Architecture; Evaluation methods; Scholarly retrieval systems; GOOGLE SCHOLAR; QUERY EXPANSION; CITATION NETWORKS; INFORMATION; PUBLICATION; COVERAGE; SCIENCE; MODELS; SCIRUS; ENGINE
제목
Comprehensive review of academic search systems: evolution, analysis, and future research directions
저자
Khalid, Shah; Almutairi, Sulaiman; Namoun, Abdallah; Khan, Jawad; Ali Khattak, Hasan; Shah, Habib
DOI
10.1007/s13278-025-01476-1
발행일
2025-07
유형
Review
저널명
SOCIAL NETWORK ANALYSIS AND MINING
권
15
호
1