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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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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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A novel deep multi-criteria collaborative filtering model for recommendation system
Knowledge-Based Systems, 2020Recommender systems have been in existence everywhere with most of them using single ratings in prediction. However, multi-criteria predictions have been proved to be more accurate. Recommender systems have many techniques; collaborative filtering is one
Nour Nassar, Assef Jafar, Yasser Rahhal
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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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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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A Survey of Recommendation Systems
Information Resources Management Journal, 2020Today's internet is able to discover almost any product or piece of information. The large amounts of unfiltered information returned by an internet query calls for filters able to validate and rank the available options. Recommender systems (RSs) are a software tool designed to qualify the options available and make suggestions that align with the ...
Sushma Malik, Anamika Rana, Mamta Bansal
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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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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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Recommendation system exploiting aspect-based opinion mining with deep learning method
Information Sciences, 2020With the developments of e-commerce websites, user textual review has become an important source of information for improving the performance of recommendation systems, as they contain fine-grained users’ opinions that generally reflect their preference ...
A. Da’u +3 more
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Learning Path Recommendation System for Programming Education Based on Neural Networks
International Journal of Distance Education Technologies, 2020Programming education has recently received increased attention due to growing demand for programming and information technology skills. However, a lack of teaching materials and human resources presents a major challenge to meeting this demand.
Tomohiro Saito, Yutaka Watanobe
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