abstract

GroupLink: Group Event Recommendations Using Personal Digital Traces

Authors:

Honghao Wei,

Cheng-Kang Hsieh,

Longqi Yang,

Deborah EstrinAuthors Info & Claims

CSCW '16 Companion: Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion

Pages 110 - 113

https://doi.org/10.1145/2818052.2874338

Published: 27 February 2016 Publication History

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Abstract

We present GroupLink, a group event recommendation system that suggests events to promote group members' face-to-face interactions in non-work settings. GroupLink addresses the challenge of finding events that appeal to a collection of individuals with diverse interests. The system mitigates the difficulties of identifying and tracking group members' preferences through analyzing and learning pref-erences from individual member's personal digital traces, including social media, email, and online streaming histo-ries. It is a web-based service that can be easily accessed using diverse devices, and is particularly suited for enhanc-ing interpersonal interactions in CSCW.

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Cited By

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Putz FHaesler SHollick M(2024)Sounds Good? Fast and Secure Contact Exchange in GroupsProceedings of the ACM on Human-Computer Interaction10.1145/36869648:CSCW2(1-44)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686964
Felfernig AAtas MStettinger MTran TReiterer S(2023)Group Recommender ApplicationsGroup Recommender Systems10.1007/978-3-031-44943-7_4(79-94)Online publication date: 23-Sep-2023
https://doi.org/10.1007/978-3-031-44943-7_4
Alvarado OHtun NJin YVerbert K(2022)A Systematic Review of Interaction Design Strategies for Group Recommendation SystemsProceedings of the ACM on Human-Computer Interaction10.1145/35551616:CSCW2(1-51)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555161
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Published In

CSCW '16 Companion: Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion

February 2016

549 pages

ISBN:9781450339506

DOI:10.1145/2818052

General Chairs:
Darren Gergle
Northwestern University
,
Meredith Ringel Morris
Microsoft Research
,
Program Chairs:
Pernille Bjørn
University of Copenhagen
,
Joseph Konstan
University of Minnesota

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 February 2016

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CSCW '16

Sponsor:

SIGCHI

CSCW '16: Computer Supported Cooperative Work and Social Computing

February 26 - March 2, 2016

California, San Francisco, USA

Acceptance Rates

Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

Upcoming Conference

CSCW '25

Sponsor:
sigchi

Computer-Supported Cooperative Work and Social Computing

October 18 - 22, 2025

Bergen , Norway

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Putz FHaesler SHollick M(2024)Sounds Good? Fast and Secure Contact Exchange in GroupsProceedings of the ACM on Human-Computer Interaction10.1145/36869648:CSCW2(1-44)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686964
Felfernig AAtas MStettinger MTran TReiterer S(2023)Group Recommender ApplicationsGroup Recommender Systems10.1007/978-3-031-44943-7_4(79-94)Online publication date: 23-Sep-2023
https://doi.org/10.1007/978-3-031-44943-7_4
Alvarado OHtun NJin YVerbert K(2022)A Systematic Review of Interaction Design Strategies for Group Recommendation SystemsProceedings of the ACM on Human-Computer Interaction10.1145/35551616:CSCW2(1-51)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555161
Wang JYang YWang SHu JWang Q(2022)Context- and Fairness-Aware In-Process Crowdworker RecommendationACM Transactions on Software Engineering and Methodology10.1145/348757131:3(1-31)Online publication date: 7-Mar-2022
https://dl.acm.org/doi/10.1145/3487571
Wang JYang YWang SChen CWang DWang Q(2022)Context-Aware Personalized Crowdtesting Task RecommendationIEEE Transactions on Software Engineering10.1109/TSE.2021.308117148:8(3131-3144)Online publication date: 1-Aug-2022
https://doi.org/10.1109/TSE.2021.3081171
Li BWang GCheng YSun YBi X(2019)An event recommendation model using ELM in event-based social networkNeural Computing and Applications10.1007/s00521-019-04344-0Online publication date: 29-Jul-2019
https://doi.org/10.1007/s00521-019-04344-0
Yang LBagdasaryan EWen HPera SEkstrand MAmatriain XO'Donovan J(2018)Modularizing deep neural network-inspired recommendation algorithmsProceedings of the 12th ACM Conference on Recommender Systems10.1145/3240323.3241618(533-534)Online publication date: 27-Sep-2018
https://dl.acm.org/doi/10.1145/3240323.3241618
Felfernig ABoratto LStettinger MTkalčič MFelfernig ABoratto LStettinger MTkalčič M(2018)Group Recommender ApplicationsGroup Recommender Systems10.1007/978-3-319-75067-5_4(75-89)Online publication date: 8-Mar-2018
https://doi.org/10.1007/978-3-319-75067-5_4

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Immersive Recommendation: News and Event Recommendations Using Personal Digital Traces

A Scalable, Accurate Hybrid Recommender System

Investigating serendipity in recommender systems based on real user feedback

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