Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence Wu, Yuzhu Herrera Triguero, Francisco Linguistic decision making Distributed linguistic representation Preference relation Multiple attribute decision making Computing with words Inteligencia artificial Artificial intelligence Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence. 2022-11-15T13:47:16Z 2022-11-15T13:47:16Z 2020-07-15 journal article Published version: Yuzhu Wu... [et al.]. Distributed linguistic representations in decision making: Taxonomy, key elements and applications, and challenges in data science and explainable artificial intelligence, Information Fusion, Volume 65, 2021, Pages 165-178, ISSN 1566-2535, [https://doi.org/10.1016/j.inffus.2020.08.018] https://hdl.handle.net/10481/77984 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elsevier