A Recommender System with Uncertainty on the Example of Political Elections

Dyczkowski, Krzysztof; Stachowiak, Anna

doi:10.1007/978-3-642-31715-6_47

Cited by 12 publications

(5 citation statements)

References 10 publications

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“…The EU Profiler and EUandI for the 2009 and 2014/2019 elections to the European Parliament respectively, used matching algorithms based on empirically defined distance matrices (Garzia et al, 2015). In addition, Dyczkowski and Stachowiak (2012) proposed a matrix based on the Hausdorff distance which is defined as the maximum distance of a set to the nearest point in the other set. Louwerse and Rosema (2014) consider a few other algorithms that are not currently used by VAAs, while one could imagine that VAAs could also use algorithms with distance matrices based on correlation or agreement coefficients.…”

Section: Matching Citizen Preferences To Political Actorsmentioning

confidence: 99%

Artificial intelligence and voting advice applications

Gemenis

2024

Front. Polit. Sci.

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The voter information tools collectively known as “Voting Advice Applications” (VAAs) have emerged as particularly popular tools in the realm of E-participation. Today, VAAs are integral parts of election campaigns in many countries around the world as they routinely engage millions of citizens, in addition to political actors and the media. This contribution assesses the integration of Artificial Intelligence (AI) in the design and dissemination of VAAs, considering normative, ethical, and methodological challenges. The study provides a comprehensive overview of AI applications in VAA development, from formulating questions to disseminating information, and concludes by highlighting areas where AI can serve as a valuable tool for enhancing the positive impact of VAAs on democratic processes.

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Section: Matching Citizen Preferences To Political Actorsmentioning

confidence: 99%

Artificial intelligence and voting advice applications

Gemenis

2024

Front. Polit. Sci.

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“…In this regard, government‐to‐citizen (G2C) is a solution where the authors in References 134‐138 propose autonomous city management to avoid such discrepancies. Citizens are encouraged to participate in public consultations where the authors in References 139‐141 present an intent‐aware voting recommender. This system links citizens to potential candidates based on their political views.…”

Section: Case Studies Of Iars For Smart Citiesmentioning

confidence: 99%

Developing smart city services using intent‐aware recommendation systems: A survey

Rafique

Hafid

Qadir

2023

Trans Emerging Tel Tech

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Smart cities could be defined as urban areas that use Information and Communication Technology (ICT) to solve city problems in efficient and sustainable ways. Intent-aware Recommender Systems (IARS) within ICT play a crucial role in filtering useless information according to user demands and assist in decision-making in various smart city platforms. In smart cities, the user traces on IoT, RFIDs, mobiles, and smart sensors capture actual user intent of performing an activity and enhance user satisfaction by proposing optimal services. This paper presents a detailed literature survey of the field of IARS and how it can be used for developing smart city services. First, we present the evolution of IARS with the development of computing technology. Then, we present case studies, synergies, advances, and a reference implementation architecture of IARS for smart cities. We discuss requirements for developing smart city services using IARS. Furthermore, we devise a comprehensive taxonomy of applications and techniques of IARS using different performance parameters. Finally, we elaborate on current issues, challenges, and future research directions in IARS; these directions we believe will pave the way for autonomous service provisioning in smart cities.

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“…With such tools, citizens are encouraged to contribute in public consultations. In this context, Terán and Meier (2010) and Dyczkowski and Stachowiak (2012) present recommendation solutions that assist voters in decision making by presenting candidates with similar political views. At the (electronic) participation level, the government offers online participation tools in which citizens propose, discuss and vote for projects and initiatives aimed to address a variety of issues and problems of a city, such as economic development, health care, education, culture, public safety, social rights, urban mobility, public transport, energy and environment.…”

Section: Recommender Systems and Smart Governancementioning

confidence: 99%