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Explanation in Recommender Systems
Artificial Intelligence Review, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Knowledge-Based Systems, 2013
Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet of things.
Jesús Bobadilla +3 more
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Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet of things.
Jesús Bobadilla +3 more
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2010
In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations.
Dietmar Jannach +3 more
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In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations.
Dietmar Jannach +3 more
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The Ethics of a Recommendation System
2014In this paper, we extend the current research in the recommendation system community by showing that users’ did attach ethical utility to items. In an experiment (N = 111) that manipulated several moral factors regarding the potentially harmful contents in movies, books and games, users were asked to evaluate the appropriateness of recommending these ...
Pinata Winoto, Tiffany Ya Tang
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Proceedings of the sixth ACM conference on Recommender systems, 2012
A recent addition to Microsoft's Xbox Live Marketplace is a recommender system which allows users to explore both movies and games in a personalized context. The system largely relies on implicit feedback, and runs on a large scale, serving tens of millions of daily users. We describe the system design, and review the core recommendation algorithm.
Noam Koenigstein +3 more
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A recent addition to Microsoft's Xbox Live Marketplace is a recommender system which allows users to explore both movies and games in a personalized context. The system largely relies on implicit feedback, and runs on a large scale, serving tens of millions of daily users. We describe the system design, and review the core recommendation algorithm.
Noam Koenigstein +3 more
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Interacting with recommender systems
CHI '99 extended abstracts on Human factors in computer systems - CHI '99, 1999Many people today live in information-rich worlds, constantly facing the question: what should I do next? Which papers should I read to learn about a new area I am interested in? Which movie should I go to? Which restaurant would I like? The experience of friends and colleagues is a valuable resource for making such decisions, especially friends who ...
Patrick Baudisch, Loren G. Terveen
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Robustness of recommender systems
Proceedings of the fifth ACM conference on Recommender systems, 2011The possibility of designing user rating profiles to deliberately and maliciously manipulate the recommendation output of a collaborative filtering system was first raised in 2002. One scenario proposed was that an author, motivated to increase recommendations of his book, might create a set of false profiles that rate the book highly, in an effort to ...
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Timeliness in recommender systems
Expert Systems with Applications, 2017Abstract Due to the high efficiency in finding the most relevant online products for users from the information ocean, recommender systems have now been applied to many commercial web sites. Meanwhile, many recommendation algorithms have been developed to improve the recommendation accuracy and diversity.
Fuguo Zhang, Qihua Liu, An Zeng
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Interacting with Recommender Systems
Companion Proceedings of the 22nd International Conference on Intelligent User Interfaces, 2017Automated recommendations have become a common feature of modern online services and mobile apps. In many practical applications, the means provided for users to interact with recommender systems (e.g., to state explicit preferences or to provide feedback on the recommendations) are, however, very limited.
Dietmar Jannach +2 more
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