@inbook{81679b5edfab44d9a2122565b3068e4e,
title = "Explanations for Groups",
abstract = "Explanations are used in recommender systems for various reasons. Users have to be supported in making (high-quality) decisions more quickly. Developers of recommender systems want to convince users to purchase specific items. Users should better understand how the recommender system works and why a specific item has been recommended. Users should also develop a more in-depth understanding of the item domain. Consequently, explanations are designed in order to achieve specific goals such as increasing the transparency of a recommendation or increasing a user{\textquoteright}s trust in the recommender system. In this chapter, we provide an overview of existing research related to explanations in recommender systems and specifically discuss aspects relevant to group recommendation scenarios. In this context, we present different ways of explaining and visualizing recommendations determined on the basis of aggregated predictions and aggregated models strategies.",
keywords = "Consensus, Explanations, Explanations for group recommender systems, Fairness",
author = "Alexander Felfernig and Nava Tintarev and {Trang Tran}, {Thi Ngoc} and Martin Stettinger",
note = "Funding Information: Support is defined by the share of attribute-specific critiques supported by an item t. i Publisher Copyright: {\textcopyright} 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2024",
month = jan,
day = "1",
doi = "10.1007/978-3-031-44943-7_6",
language = "English",
series = "Signals and Communication Technology",
publisher = "Springer",
pages = "109--131",
booktitle = "Group Recommender Systems",
address = "United States",
}