short-paper

Recommender systems for citizens: the CitRec'17 workshop manifesto

Authors:

Iván Cantador,

Diana Nurbakova,

María E. Cortés-Cediel,

Alessandro BozzonAuthors Info & Claims

CitRec '17: Proceedings of the International Workshop on Recommender Systems for Citizens

Article No.: 1, Pages 1 - 4

https://doi.org/10.1145/3127325.3177871

Published: 31 August 2017 Publication History

Abstract

This manifesto summarises the outcomes of the 1st Workshop on Recommender Systems for Citizens (CitRec'17), held at the 11th ACM Conference on Recommender Systems, in August 2017 in Como, Italy. We discuss challenges and opportunities for the development of recommender systems for citizens, including: the clarification of the role of recommender systems for cities and citizens; in this context, the identification of classes of items to be recommended; the need for targeting and engaging the right population, involving the right stakeholders; and the existence of underlying ethical issues such as fairness and consensus. We further provide an action plan to bring forward the research and application of recommender systems for citizens.

References

[1]

Sherry R Arnstein. 1969. A ladder of citizen participation. Journal of the American Institute of Planners 35, 4 (1969), 216--224.

[2]

Tarek Awwad, Nadia Bennani, Konstantin Ziegler, Veronika Sonigo, Lionel Brunie, and Harald Kosch. 2017. Efficient Worker Selection Through History-Based Learning in Crowdsourcing. In Proceedings of 41st IEEE Annual Computer Software and Applications Conference (COMPSAC '17), Volume 1. 923--928.

[3]

Iván Cantador, Alejandro Bellogín, María E. Cortés-Cediel, and Olga Gil. 2017. Personalized Recommendations in E-participation: Offline Experiments for the 'Decide Madrid' Platform. In Proceedings of the 1st Workshop on Recommender Systems for Citizens (CitRec '17).

Digital Library

[4]

Fran Casino, Edgar Batista, Constantinos Patsakis, and Agusti Solanas. 2015. Context-aware recommender for smart health. In Proceedings of the IEEE 1st International Smart Cities Conference (ISC2 '15). IEEE, 1--2.

[5]

Cen Chen, Shih-Fen Cheng, Hoong Chuin Lau, and Archan Misra. 2015. Towards City-scale Mobile Crowdsourcing: Task Recommendations under Trajectory Uncertainties. In Proceedings of the 24th International Joint Conferences on Artificial Intelligence.

Digital Library

[6]

María E. Cortés-Cediel, Iván Cantador, and Olga Gil. 2017. Recommender systems for e-governance in smart cities: State of the art and research opportunities. In Proceedings of the 1st Workshop on Recommender Systems for Citizens (CitRec '17).

Digital Library

[7]

André Sales Fonteles, Sylvain Bouveret, and Jérôme Gensel. 2014. Towards Matching Improvement Between Spatio-temporal Tasks and Workers in Mobile Crowdsourcing Market Systems. In Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems. ACM, New York, NY, USA, 43--50.

Digital Library

[8]

Luke Wayne Henderson, Tess Knight, and Ben Richardson. 2013. The Hedonic and Eudaimonic Validity of the Orientations to Happiness Scale. Social Indicators Research 115, 3 (2013), 1087--1099.

[9]

Longke Hu, Aixin Sun, and Yong Liu. 2014. Your neighbors affect your ratings: on geographical neighborhood influence to rating prediction. In Proceedings of the 37th International ACM SIGIR conference on Research & Development in Information Retrieval. ACM, 345--354.

Digital Library

[10]

Dietmar Jannach and Gediminas Adomavicius. 2016. Recommendations with a Purpose. In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys '16). ACM, 7--10.

Digital Library

[11]

Yehuda Koren. 2010. Collaborative filtering with temporal dynamics. Commun. ACM 53, 4 (2010), 89--97.

Digital Library

[12]

Diana Nurbakova, Léa Laporte, Sylvie Calabretto, and Jérôme Gensel. 2017. Users Psychological Profiles for Leisure Activity Recommendation: User Study. In Proceedings of the 1st Workshop on Recommender Systems for Citizens (CitRec 17).

Digital Library

[13]

Christopher Peterson, Nansook Park, and Martin E. P. Seligman. 2005. Orientations to happiness and life satisfaction: the full life versus the empty life. Journal of Happiness Studies 6, 1 (March 2005), 25--41.

[14]

Jennifer Rowley. 2011. e-Government stakeholders - Who are they and what do they want? International Journal of Information Management 31, 1 (2011), 53--62.

Digital Library

[15]

Salvador Ruiz-Correa, Darshan Santani, Beatriz Ramirez-Salazar, Itzia Ruiz-Correa, Fatima Alba Rendon-Huerta, Carlo Olmos-Carrillo, Brisa Carmina Sandoval-Mexicano, Angel Humberto Arcos-Garcia, Rogelio Hasimoto-Beltrán, and Daniel Gatica-Perez. 2017. SenseCityVity: Mobile Crowdsourcing, Urban Awareness, and Collective Action in Mexico. IEEE Pervasive Computing 16, 2 (2017), 44--53.

Digital Library

[16]

Mao Ye, Peifeng Yin, Wang-Chien Lee, and Dik-Lun Lee. 2011. Exploiting geographical influence for collaborative point-of-interest recommendation. In Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval. ACM, 325--334.

Digital Library

[17]

Yu Zheng and Xing Xie. 2011. Learning travel recommendations from user-generated GPS traces. ACM Transactions on Intelligent Systems and Technology (TIST) 2, 1 (2011), 2.

Digital Library

[18]

Haiyi Zhu, Robert Kraut, and Aniket Kittur. 2012. Organizing Without Formal Organization: Group Identification, Goal Setting and Social Modeling in Directing Online Production. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work (CSCW '12). ACM, 935--944.

Digital Library

Cited By

Andrade-Ruiz GCarrasco RPorcel CSerrano-Guerrero JMata FArias-Oliva M(2024)Emerging Perspectives on the Application of Recommender Systems in Smart CitiesElectronics10.3390/electronics1307124913:7(1249)Online publication date: 27-Mar-2024
https://doi.org/10.3390/electronics13071249
Campos SFigueiredo J(2023)Public services recommendation system: an alternative to customize the digital government transformationProceedings of the 24th Annual International Conference on Digital Government Research10.1145/3598469.3598511(370-379)Online publication date: 11-Jul-2023
https://dl.acm.org/doi/10.1145/3598469.3598511

Index Terms

Recommender systems for citizens: the CitRec'17 workshop manifesto
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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CitRec 2017: International Workshop on Recommender Systems for Citizens
RecSys '17: Proceedings of the Eleventh ACM Conference on Recommender Systems

The "International Workshop on Recommender Systems for Citizens" (CitRec) is focused on a novel type of recommender systems both in terms of ownership and purpose: recommender systems run by citizens and serving society as a whole.
Acquiring User Information Needs for Recommender Systems
WI-IAT '13: Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) - Volume 03

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based ...

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Information & Contributors

Information

Published In

cover image ACM Other conferences

CitRec '17: Proceedings of the International Workshop on Recommender Systems for Citizens

August 2017

38 pages

ISBN:9781450353700

DOI:10.1145/3127325

Conference Chairs:
Jie Yang
Delft University of Technology, Netherlands
,
Zhu Sun
Nanyang Technological University, Singapore
,
Alessandro Bozzon
Delft University of Technology, Netherlands
,
Jie Zhang
Nanyang Technological University, Singapore
,
Martha Larson
Radboud University Nijmegen, Netherlands

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 31 August 2017

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CitRec: International Workshop on Recommender Systems for Citizens

August 31, 2017

Como, Italy

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Cited By

Andrade-Ruiz GCarrasco RPorcel CSerrano-Guerrero JMata FArias-Oliva M(2024)Emerging Perspectives on the Application of Recommender Systems in Smart CitiesElectronics10.3390/electronics1307124913:7(1249)Online publication date: 27-Mar-2024
https://doi.org/10.3390/electronics13071249
Campos SFigueiredo J(2023)Public services recommendation system: an alternative to customize the digital government transformationProceedings of the 24th Annual International Conference on Digital Government Research10.1145/3598469.3598511(370-379)Online publication date: 11-Jul-2023
https://dl.acm.org/doi/10.1145/3598469.3598511

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