Francesco Ricci

Séamus Lawless

Kalina Bontcheva

Owen Conlan

This book constitutes the refereed proceedings of the 23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015, held in Dublin, Ireland, in June/July 2015. The 25 long and 7 short papers of the research paper track were carefully reviewed and selected from 112 submissions. The papers reflect the conference theme "Contextualizing the World", highlighting the significance and impact of user modeling and adaptive technologies on a large number of everyday application areas such as: intelligent learning environments, recommender systems, e-commerce, advertising, personalized information retrieval and access, digital humanities, e-government, cultural heritage, and personalized health.

23rd International Conference, UMAP 2015, Dublin, Ireland, June 29 -- July 3, 2015. Proceedings

User Modeling, Adaptation and Personalization

Lior Rokach

Bracha Shapira

Paul B. Kantor

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments. Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included. Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.

Recommender Systems Handbook

Anna Achmatova, Alda Merini, Antonia Pozzi

Tre donne

profili letterari di poeti italiani del Novecento

Il nulla e la luce

Da ogni dove e in nessun luogo

Corso teorico-pratico di diritto civile

This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.

Tsvi Kuflik

Geert-Jan Houben

Vania Dimitrova

David Chin

Peter Dolog

This book constitutes the thoroughly refereed proceedings of the 22nd International Conference on User Modeling, Adaption and Personalization, held in Aalborg, Denmark, in July 2014. The 23 long and 19 short papers of the research paper track were carefully reviewed and selected from 146 submissions. The papers cover the following topics: large scale personalization, adaptation and recommendation; Personalization for individuals, groups and populations; modeling individuals, groups and communities; Web dynamics and personalization; adaptive web-based systems; context awareness; social recommendations; user experience; user awareness and control; Affective aspects; UMAP underpinning by psychology models; privacy; perceived security and trust; behavior change and persuasion.

22nd International Conference, UMAP 2014, Aalborg, Denmark, July 7-11, 2014. Proceedings

Francesco Ricci

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