Recommender System Based On Linked Data
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Recommender System based on linked Data
Author: Figueroa, Cristhian
language: en
Publisher: Editorial Universidad del Cauca
Release Date: 2019-12-13
Linked Data principles have led to semantically interlink and connect different resourcesat data level regardless the structure, authoring, location etc. Data available on the Web using Linked Data has resulted in a global data space called the Web of Data. Moreover, thanks to the efforts of the scientific community and the W3C Linked Open Data (LOD) project, more and more data have been published on the Web of Data, helping its growth and evolution. This book studies Recommender Systems that use LInked Data as a source for generating recommendations exploiting the large amount of available resources and the relationships between them. Firts, a comprehensive state of the art is preseted in order to indetify and study frameworks and algorithms for RS that rely on Linked Data. Second a framework named AlLied taht makes available implementations of the most used algortihms for resource recommendation based on Linked Data is described. This framework is inteded to use and test the recommendation algorithms in various domains and contexts, and to analyze their behavior under different conditions. Accordingly the framework is suitable to compare the results of these algorithms both in performance and relevance, and to enable the development of innovative applications on top of it.
Recommender Systems
This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors.
Availability, Reliability, and Security in Information Systems and HCI
This book constitutes the refereed proceedings of the IFIP WG 8.4, 8.9, TC 5 International Cross-Domain Conference on Availability, Reliability and Security, CD-ARES 2013, held in Regensburg, Germany, in September 2013. The 21 revised papers presented were carefully reviewed and selected for inclusion in the volume. The papers concentrate on the many aspects of information systems bridging the gap between research results in computer science and the many application fields. They are organized in the following topical sections: economic, ethical, legal, multilingual, organizational and social aspects; context-oriented information integration; data/information management as a service; context-oriented information integration and location-aware computing; security and privacy; risk management and business continuity; and security and privacy and location based applications. Also included are 15 papers from a special session on Human-Computer Interaction and Knowledge Discovery (HCI-KDD 2013).