Call for Book Chapters

Book Title: Research Discovery by Integrating Recommenders with Scientometrics

Publisher: Springer Nature

Editors:

1. Chaker Jebari, University of Technology and Applied Sciences, Oman (Email: jebarichaker@yahoo.fr)
2. Dimitrios Katsaros, University of Thessaly, Volos, Greece (Email: dkatsar@uth.gr)
3. Yannis Manolopoulos, University of York, Europe Campus, Thessaloniki, Greece (Email: imanolopoulos@city.yorkeuropecampus.eu)

Corresponding Editor: Chaker Jebari (Email: jebarichaker@yahoo.fr )

Book Overview

The rapid growth of scholarly publications has made research discovery increasingly complex. Traditional search methods often fail to capture relevant literature efficiently or reveal emerging trends. Recommendation systems, providing tailored research suggestions, and scientometric methods, offering quantitative insights into the structure and impact of scientific knowledge, represent complementary strategies to address these challenges.

This volume explores the integration of recommender systems and scientometrics to enhance research discovery, literature review, and scientific evaluation. It seeks contributions on novel algorithms, methodologies, evaluation frameworks, Artificial Intelligence and Language Models-based approaches, and other practical approaches that leverage this integration. This book will provide a comprehensive reference for researchers, practitioners, and policymakers in information science, computer science, and related fields.

Important Dates

• Chapter proposal submission: 31 March 2026
• Notification of proposal acceptance: 20 April 2026
• Full chapter submission: 1^st July 2026
• Review feedback: 1^st October 2026
• Revised chapter submission: 1^st November 2026
• Final acceptance notification: 1^st December 2026

Objectives

The main objectives of this book are to:

• Advance research on scholarly recommender systems and research discovery
• Integrate scientometric indicators into recommendation and ranking models
• Explore the role of AI and LLMs in literature discovery and review automation
• Provide evaluation frameworks, benchmarks, and user-centered studies
• Address transparency, bias, fairness, and ethical issues in research discovery

Scope and Topics

We invite original, high-quality chapter proposals addressing theoretical, methodological, and applied aspects of the integration of recommender systems and scientometrics, including but not limited to:

• Scholarly recommender systems (articles, authors, venues, datasets)
• Citation and reference recommendation
• Scientometrics and bibliometrics for research discovery
• Hybrid literature discovery approaches, including Machine Learning and scientometrics techniques
• Knowledge graphs for scholarly exploration
• Large language models (LLMs) in literature discovery
• Automation of systematic literature reviews
• Research trend detection and topic evolution
• Explainable and interpretable recommendations
• Evaluation metrics, datasets, and benchmarks
• User studies and human-centered evaluation
• Bias, fairness, and ethical considerations
• Case studies of academic or commercial platforms

Target Audience

• Researchers and PhD students in Information Science, Computer Science, Data Science, and Scientometrics
• Developers of scholarly search and recommendation systems
• Librarians, research managers, and science policy analysts

Submission Guidelines

• Chapters should be 20 pages at most, including references.
• All submissions must be written in English.
• Chapters must present original, unpublished work and must not be under consideration elsewhere.
• All submissions will undergo a peer-review process in accordance with Springer’s editorial standards.
• Accepted chapters must follow the Springer chapter formatting template that can be downloaded from this link: https://www.springernature.com/gp/authors/publish-a-book/manuscript-guidelines

Submission Procedure

Authors are invited to submit a chapter proposal of 1000 words including:

• Chapter title
• Abstract
• Keywords
• Author(s) names and affiliations

Publication Information

Accepted chapters will be published in an edited volume by Springer Nature. The book will be available in both print and electronic formats and indexed according to Springer’s standard indexing services.