Comprehensive review of academic search systems
Evolution, analysis, and future research directions
Bibliographic Data
| ID | 16858697 |
|---|---|
| Authors | Shah Khalid (0000-0003-3538-3905), Sulaiman Almutairi (0000-0002-3373-281X), Abdallah Namoun (0000-0002-7050-0532), Jawad Khan (0000-0002-8340-1357), Hasan Ali Khattak (0000-0002-8198-9265), Habib Shah (0000-0003-2078-6285) |
| Year | 2025 |
| Volume | 15 |
| Issue | 1 |
| Publication date | 2025-07-04 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-025-01476-1 |
| OpenAlex | W4411989402 |
| Language | EN |
| References cited | 114 |
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
Biology · Computational biology · Data science · Management science · Advanced Text Analysis Techniques · Computer Science · Engineering · Information Retrieval and Search Behavior · Web Data Mining and Analysis
Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation—Review of the Literature
Undertaking a literature review
Google Scholar to overshadow them all? Comparing the sizes of 12 academic search engines and bibliographic databases
Which academic search systems are suitable for systematic reviews or meta‐analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources
The anatomy of a large-scale hypertextual Web search engine
The rate of growth in scientific publication and the decline in coverage provided by Science Citation Index
Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ Coci
| Highly cited | No |
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