Applied Machine Learning for Information Retrieval
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 31 January 2025 | Viewed by 130
Special Issue Editors
Interests: data mining; machine learning; recommender systems; social network analysis; text mining; semi-structured data analysis
Special Issues, Collections and Topics in MDPI journals
Interests: data mining; machine learning; recommender systems; social network/media analysis; text mining; semistructured data analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Searching through, organizing, and interpreting information has advanced significantly due to machine learning and information retrieval integration. Given the exponential growth of digital content, applying machine learning approaches to information retrieval is crucial for improving search relevancy, user experience, and data management. This Special Issue will present approaches and techniques that address current issues and pave the way for future research, with the goal being to showcase machine learning research and practical applications in the field of information retrieval.
We welcome submissions demonstrating how machine learning is beneficially utilized in different fields of information retrieval, such as search engines, recommendation systems, natural language processing, and multimedia retrieval. This Special Issue's topics of interest encompass, but are not restricted to, the following:
- Search and ranking algorithms
- Recommendation systems
- Natural language processing (NLP)
- Image and video retrieval
- User behavior modeling
- Information extraction
- Big data analytics
- Security and privacy
- Evaluation metrics and benchmarks
- Large language models (LLMs)
Dr. Gianni Costa
Dr. Riccardo Ortale
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
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Keywords
- search and ranking algorithms
- recommendation systems
- natural language processing (NLP)
- image and video retrieval
- user behavior modeling
- information extraction
- big data analytics
- security and privacy
- evaluation metrics and benchmarks
- large language models (LLMs)
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