demonstration

CHARM: a Group Decision Making Support Chatbot

Authors:

Amra Delic,

Hanif Emamgholizadeh,

Thuy Ngoc Nguyen,

Francesco RicciAuthors Info & Claims

IUI '24 Companion: Companion Proceedings of the 29th International Conference on Intelligent User Interfaces

Pages 7 - 10

https://doi.org/10.1145/3640544.3645220

Published: 05 April 2024 Publication History

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Abstract

Messaging apps, such as Telegram and WhatsApp, are routinely used to communicate, chat and make decisions. Group Recommender Systems (GRSs) have been introduced as self standing tools to support group interactions and decision-making. We present here a TelegramBot, named CHARM, that supports groups to make a decision on an arbitrary topic by leveraging GRSs techniques. CHARM helps elicit the group members’ preferences, ranks the items that the members have suggested to be considered, provides a summary of the current status of the discussion, and finally recommends a fair choice. A focus group study has revealed that the designed functionality includes features that users expect to find in a bot aimed at supporting group decision-making.

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Cited By

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Emamgholizadeh HDelić ARicci FBoratto LGena CMarras MGermanakos PPopescus E(2024)Anticipating Eating Preferences in Group Decision MakingAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664894(329-336)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3631700.3664894
Alves PMartins ANegrão FNovais PAlmeida AMarreiros G(2024)Are heterogeinity and conflicting preferences no longer a problem? Personality-based dynamic clustering for group recommender systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124812255:PDOnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.124812

Index Terms

CHARM: a Group Decision Making Support Chatbot
1. Information systems
  1. Information retrieval
    1. Users and interactive retrieval
      1. Collaborative search

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Published In

IUI '24 Companion: Companion Proceedings of the 29th International Conference on Intelligent User Interfaces

March 2024

182 pages

ISBN:9798400705090

DOI:10.1145/3640544

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 05 April 2024

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March 18 - 21, 2024

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Emamgholizadeh HDelić ARicci FBoratto LGena CMarras MGermanakos PPopescus E(2024)Anticipating Eating Preferences in Group Decision MakingAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664894(329-336)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3631700.3664894
Alves PMartins ANegrão FNovais PAlmeida AMarreiros G(2024)Are heterogeinity and conflicting preferences no longer a problem? Personality-based dynamic clustering for group recommender systemsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124812255:PDOnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.124812

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Consensus-based decision support for multicriteria group decision making

Anticipating Eating Preferences in Group Decision Making

Recommending items to group of users using Matrix Factorization based Collaborative Filtering

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