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Title Details:
Intelligent Recommender Systems
Other Titles: Data Mining, Information Retrieval, Machine Learning and Artificial Intelligence Algorithms
Authors: Symeonidis, Panagiotis
Subject: MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INFORMATION MANAGEMENT > DATA MINING
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INFORMATION MANAGEMENT > INFORMATION STORAGE AND RETRIEVAL
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS > BASIC MACHINE LEARNING
MATHEMATICS AND COMPUTER SCIENCE > COMPUTER SCIENCE > INTELLIGENT SYSTEMS > ADVANCED MACHINE LEARNING
Keywords:
Recommender systems
Intelligent systems
Machine learning
Data mining
Information Retrieval
Description:
Abstract:
This book is intended to cover a relatively new scientific field, which has not received the required attention of the lecturers in the Computer Science and Computer Engineering departments of the Greek Universities. This work presents in detail the most important algorithms of the last 20 years from the main scientific fields of Information Retrieval, Machine Learning, Data Mining and Artificial Intelligence, which have influenced and shaped Recommendation Systems. The timing of its publication can be described as mature, given that the author has been carrying out research work for almost 20 years (since 2005) in the scientific field of Recommendation Systems.
Linguistic Editors: Sakellarios, Michalis
Technical Editors: Karatzidis, Dimitrios
Graphic Editors: Symeonidis, Panagiotis
Type: Postgraduate textbook
Creation Date: 04-01-2023
Item Details:
ISBN 978-618-5726-37-9
License: Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0)
DOI http://dx.doi.org/10.57713/kallipos-156
Handle http://hdl.handle.net/11419/8906
Bibliographic Reference: Symeonidis, P. (2023). Intelligent Recommender Systems [Postgraduate textbook]. Kallipos, Open Academic Editions. https://dx.doi.org/10.57713/kallipos-156
Language: Greek
Consists of:
1. Introduction to Recommender Systems
2. Collaborative Filtering Algorithms
3. Content-based Filtering Algorithms
4. Context-aware Recommender Systems
5. Matrix Factorization Algorithms
6. Machine Learning with Neural Nets
7. Deep Reinforcement Learning and Genetic Algorithms
8. Graph-based Recommender Systems
9. Evaluation Metrics
10. New Trends
Number of pages 356
Publication Origin: Kallipos, Open Academic Editions
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