Francesco Ricci spends much of his time researching Recommender system, World Wide Web, Collaborative filtering, Information retrieval and Process. His work carried out in the field of Recommender system brings together such families of science as User modeling, Personalization, Multimedia, Human–computer interaction and RSS. His World Wide Web study combines topics in areas such as Contextual information, User assistance, Ranking and Mobile computing.
His Collaborative filtering research includes themes of Active learning, Order, Data mining and Relevance. His research investigates the connection between Information retrieval and topics such as Data set that intersect with issues in k-nearest neighbors algorithm, Contextual variable and Context based. His biological study spans a wide range of topics, including Industrial organization and Artificial intelligence, Reinforcement learning.
His primary areas of study are Recommender system, World Wide Web, Information retrieval, Human–computer interaction and Collaborative filtering. Francesco Ricci combines subjects such as Quality, Data mining, Multimedia, Artificial intelligence and RSS with his study of Recommender system. His World Wide Web research integrates issues from Contextual information, User modeling, Mobile computing and Set.
His Information retrieval research is multidisciplinary, relying on both Similarity and Order. His work on Usability as part of general Human–computer interaction study is frequently linked to Graphical user interface, therefore connecting diverse disciplines of science. His Cold start study in the realm of Collaborative filtering connects with subjects such as Matrix decomposition.
The scientist’s investigation covers issues in Recommender system, World Wide Web, Human–computer interaction, Information retrieval and Preference elicitation. His study on Collaborative filtering is often connected to Group as part of broader study in Recommender system. His World Wide Web study combines topics from a wide range of disciplines, such as Decision-making, Preference learning, Mood, Decision support system and Usability.
The various areas that he examines in his Human–computer interaction study include Software development, Context model and Set. His Information retrieval research includes elements of RSS, Cluster analysis and Inverse reinforcement learning. His Preference elicitation research focuses on Cold start and how it connects with Feature and Feature based.
His scientific interests lie mostly in Recommender system, World Wide Web, Information retrieval, Human–computer interaction and Group. His Recommender system research incorporates elements of Order, Decision-making and Usability. Within one scientific family, Francesco Ricci focuses on topics pertaining to Preference learning under World Wide Web, and may sometimes address concerns connected to Reinforcement learning and User modeling.
His Information retrieval research incorporates themes from Affect, Mood, Preference elicitation, Decision support system and Information and Communications Technology. He has included themes like Context model, Data mining and Software development in his Human–computer interaction study. His study in Task is interdisciplinary in nature, drawing from both Aggregation problem and Data science.
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Introduction to Recommender Systems Handbook
Francesco Ricci;Lior Rokach;Bracha Shapira.
Recommender Systems Handbook (2011)
Recommender Systems Handbook
Francesco Ricci;Lior Rokach;Bracha Shapira;Paul B. Kantor.
Context-Aware Recommender Systems
Gediminas Adomavicius;Bamshad Mobasher;Francesco Ricci;Alexander Tuzhilin.
Ai Magazine (2011)
Recommender Systems: Introduction and Challenges
Francesco Ricci;Lior Rokach;Bracha Shapira.
Recommender Systems Handbook (2015)
E-commerce and tourism
Hannes Werthner;Francesco Ricci.
Communications of The ACM (2004)
Group recommendations with rank aggregation and collaborative filtering
Linas Baltrunas;Tadas Makcinskas;Francesco Ricci.
conference on recommender systems (2010)
Mobile recommender systems.
Information Technology & Tourism (2010)
Matrix factorization techniques for context aware recommendation
Linas Baltrunas;Bernd Ludwig;Francesco Ricci.
conference on recommender systems (2011)
Context relevance assessment and exploitation in mobile recommender systems
Linas Baltrunas;Bernd Ludwig;Stefan Peer;Francesco Ricci.
ubiquitous computing (2012)
Improving recommender systems with adaptive conversational strategies
Tariq Mahmood;Francesco Ricci.
acm conference on hypertext (2009)
Profile was last updated on December 6th, 2021.
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