• Publications
  • Influence
Introduction to Recommender Systems Handbook
TLDR
The main goal is to delineate, in a coherent and structured way, the chapters included in this handbook and to help the reader navigate the extremely rich and detailed content that the handbook offers.
Group recommendations with rank aggregation and collaborative filtering
TLDR
It is observed that the effectiveness of a group recommendation does not necessarily decrease when the group size grows, and the more alike the users in the group are, the more effective the group recommendations are.
Matrix factorization techniques for context aware recommendation
TLDR
A novel context-aware recommendation algorithm that extends Matrix Factorization is presented that has the advantage of smaller computational cost and provides the possibility to represent at different granularities the interaction between context and items.
Recommender Systems: Introduction and Challenges
TLDR
This introductory chapter briefly discusses basic RS ideas and concepts and aims to delineate, in a coherent and structured way, the chapters included in this handbook.
Recommender Systems Handbook
TLDR
This handbook illustrates how recommender systems can support the user in decision-making, planning and purchasing processes, and works for well known corporations such as Amazon, Google, Microsoft and AT&T.
E-commerce and tourism
Travel and tourism are illustrating how e-commerce can change the structure of an industry---and in the process create new business opportunities.
InCarMusic: Context-Aware Music Recommendations in a Car
TLDR
In this paper, the individual perceptions of the users about the influence of context on their decisions are considered and it is shown that it is possible to build an effective context-aware mobile recommender system.
Context-Aware Recommender Systems
TLDR
An overview of the multifaceted notion of context is provided, several approaches for incorporating contextual information in recommendation process are discussed, and the usage of such approaches in several application areas where different types of contexts are exploited are illustrated.
Mobile Recommender Systems
  • F. Ricci
  • Computer Science
    J. Inf. Technol. Tour.
  • 1 April 2010
TLDR
The major issues and opportunities that the mobile scenario opens to the application of recommender systems especially in the area of travel and tourism are reviewed and some possible future developments and extension are presented.
Context relevance assessment and exploitation in mobile recommender systems
TLDR
A context-aware mobile recommender system that utilizes the contextual factors shown to be important and was preferred to a similar variant that did not exploit contextual information in a subsequent user evaluation.
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