Information Retrieval: From Theory to Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 April 2026 | Viewed by 12
Special Issue Editors
Interests: information retrieval; machine learning; computer vision; multimedia retrieval; quantum machine learning
Interests: privacy; access control; blockchain; social network analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue explores the rapidly evolving field of information retrieval (IR), bridging foundational theory with cutting-edge applications. We delve into how modern techniques and technologies, particularly those emerging from the field of natural language processing (NLP), are transforming traditional IR systems. The Special Issue covers the integration of Large Language Models (LLMs) to enhance query understanding and response generation, exploring frameworks like Retrieval-Augmented Generation (RAG) that ground LLM outputs in factual, external data. We also examine the critical role of Rerankers in refining search results for superior relevance. Additionally, we investigate how IR principles are fundamental to the design and implementation of modern recommender systems, which personalize content and suggestions. This collection of research provides a comprehensive overview of the current landscape, addressing challenges and showcasing innovative solutions from academia and industry.
Dr. Amit Kumar Jaiswal
Dr. Gianluca Lax
Guest Editors
Manuscript Submission Information
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Keywords
- information retrieval
- large language models
- retrieval augmented generation
- reranking
- semantic search
- query understanding
- recommender systems
- personalisation
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