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CitRec '17: Proceedings of the International Workshop on Recommender Systems for Citizens
ACM2017 Proceeding
  • Conference Chairs:
  • Jie Yang,
  • Zhu Sun,
  • Alessandro Bozzon,
  • Jie Zhang,
  • Martha Larson
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
CitRec: International Workshop on Recommender Systems for Citizens Como Italy 31 August 2017
ISBN:
978-1-4503-5370-0
Published:
31 August 2017

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Abstract

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short-paper
Recommender systems for citizens: the CitRec'17 workshop manifesto

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 ...

research-article
Revisiting revisits in trajectory recommendation

Trajectory recommendation is the problem of recommending a sequence of places in a city for a tourist to visit. It is strongly desirable for the recommended sequence to avoid loops, as tourists typically would not wish to revisit the same location. ...

research-article
Users psychological profiles for leisure activity recommendation: user study

Leisure activities are essential in the individual's pursuit of well-being and higher satisfaction with life. In the last few years, the event-based social networks and event-promoting services on Face-book, Couchsurfing etc., have seen a boosting use. ...

research-article
Bumblebee friendly planting recommendations with citizen science data

Several citizen science projects engage with the public around pollinator species, typically requesting data (e.g. in the form of photo-records of different species tagged by place and date). While such projects help scientists collect data, these data ...

research-article
Personalized recommendations in e-participation: offline experiments for the 'Decide Madrid' platform

In e-participation platforms, citizens suggest, discuss and vote online for initiatives aimed to address a wide range of issues and problems in a city, such as economic development, public safety, budges, infrastructure, housing, environment, social ...

short-paper
Chatbots as conversational recommender systems in urban contexts

In this paper, we outline the vision of chatbots that facilitate the interaction between citizens and policy-makers at the city scale. We report the results of a co-design session attended by more than 60 participants. We give an outlook of how some ...

research-article
Recommender systems for e-governance in smart cities: state of the art and research opportunities

E-governance can be considered as the core and most important challenge of smart cities initiatives. It refers to the use of information and communication technologies in the public sector with the aim of improving information and service delivery, ...

Contributors
  • A-Star, Institute of High Performance Computing
  • Delft University of Technology
  • Radboud University
  1. Proceedings of the International Workshop on Recommender Systems for Citizens

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