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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…mehr

Produktbeschreibung
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.

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Autorenporträt
Cristhian Figueroa He received the B.S. degree in electronics and telecommunications engineering, the MSc and PhD degrees in telematics from Universidad del Cauca (Colombia) in 2008, 2012, and 2017, respectively. He also holds a PhD in informatics and systems engineering from Politecnico di Torino (Italy) in 2017. He is an experienced researcher, who has participated in national and international projects in Colombia and Italy. He is currently a teacher and researcher at the Department of Telematics at the Universidad del Cauca. His research interests include semantic web, recommender systems, machine learning, mobile information systems, IoT and business process discovery. Maurizio Morisio He received the PhD degree in software engineering and the MSc degree in electronic engineering from the Politecnico di Torino. He is full professor at the Politecnico di Torino, Turin, Italy. Previously he spent two years working as consultant at IGL Technology, Paris. And two years as researcher with the Experimental Software Engineering Group at the University of Maryland, College Park. His interest lies in finding, applying and evaluating the most suitable techniques and processes to produce better software, faster. Juan Carlos Corrales He is Electronics and Telecommunications Engineer, Universidad del Cauca, Colombia. Master in Telematics engineering, Universidad del Cauca, Colombia. Doctor in Computer Science, University of Versailles SaintQuentin-en-Yvelines, France. Full Professor and Leader of the Telematics Engineering Group at Universidad del Cauca, Colombia.