17   Artículos

 
en línea
Dionisis Margaris, Costas Vassilakis, Dimitris Spiliotopoulos and Stefanos Ougiaroglou    
Collaborative filtering has proved to be one of the most popular and successful rating prediction techniques over the last few years. In collaborative filtering, each rating prediction, concerning a product or a service, is based on the rating values tha... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Dimitris Koryzis, Dionisis Margaris, Costas Vassilakis, Konstantinos Kotis and Dimitris Spiliotopoulos    
Exploitation and use of disruptive technologies, such as the Internet of Things, recommender systems, and artificial intelligence, with an ambidextrous balance, are a challenge, nowadays. Users of the technologies, and stakeholders, could be part of a ne... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Vasilis Bouras, Dimitris Spiliotopoulos, Dionisis Margaris, Costas Vassilakis, Konstantinos Kotis, Angeliki Antoniou, George Lepouras, Manolis Wallace and Vassilis Poulopoulos    
Digital assistants?such as chatbots?facilitate the interaction between persons and machines and are increasingly used in web pages of enterprises and organizations. This paper presents a methodology for the creation of chatbots that offer access to museu... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Dimitris Spiliotopoulos, Dionisis Margaris and Costas Vassilakis    
One of the typical goals of collaborative filtering algorithms is to produce rating predictions with values very close to what real users would give to an item. Afterward, the items having the largest rating prediction values will be recommended to the u... ver más
Revista: Information    Formato: Electrónico

 
en línea
Dionisis Margaris, Dimitris Spiliotopoulos, Gregory Karagiorgos and Costas Vassilakis    
Collaborative filtering algorithms formulate personalized recommendations for a user, first by analysing already entered ratings to identify other users with similar tastes to the user (termed as near neighbours), and then using the opinions of the near ... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Dimitris Spiliotopoulos, Dionisis Margaris and Costas Vassilakis    
User experience design and subsequent usability evaluation can benefit from knowledge about user interaction, types, deployment settings and situations. Most of the time, the user type and generic requirements are given or can be obtained and used to mod... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Kimon Deligiannis, Paraskevi Raftopoulou, Christos Tryfonopoulos, Nikos Platis and Costas Vassilakis    
Advancements in cultural informatics have significantly influenced the way we perceive, analyze, communicate and understand culture. New data sources, such as social media, digitized cultural content, and Internet of Things (IoT) devices, have allowed us... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Costas Vassilakis, Konstantinos Kotis, Dimitris Spiliotopoulos, Dionisis Margaris, Vlasios Kasapakis, Christos-Nikolaos Anagnostopoulos, Georgios Santipantakis, George A. Vouros, Theodore Kotsilieris, Volha Petukhova, Andrei Malchanau, Ioanna Lykourentzou, Kaj Michael Helin, Artem Revenko, Nenad Gligoric and Boris Pokric    
This paper presents SemMR, a semantic framework for modelling interactions between human and non-human entities and managing reusable and optimized cultural experiences, towards a shared cultural experience ecosystem that might seamlessly accommodate mix... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Costas Vassilakis and Dionisis Margaris    
Revista: Information    Formato: Electrónico

 
en línea
Dionisis Margaris and Costas Vassilakis    
One of the major problems that social networks face is the continuous production of successful, user-targeted information in the form of recommendations, which are produced exploiting technology from the field of recommender systems. Recommender systems ... ver más
Revista: Informatics    Formato: Electrónico

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