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Matching Theory-based Recommender Systems in Online Dating

Authors:

Yoji Tomita,

Riku Togashi,

Daisuke MoriwakiAuthors Info & Claims

RecSys '22: Proceedings of the 16th ACM Conference on Recommender Systems

Pages 538 - 541

https://doi.org/10.1145/3523227.3547406

Published: 13 September 2022 Publication History

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Cited By

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Tomita YYokoyama T(2024)Fair Reciprocal Recommendation in Matching MarketsProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688130(209-218)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688130
Yang CDai SHou YZhao WXu JSong YZhu HBaeza-Yates RBonchi F(2024)Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and MethodProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671734(3714-3723)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671734
Felfernig AWundara MTran TPolat-Erdeniz SLubos SEl Mansi MGarber DLe V(2023)Recommender systems for sustainability: overview and research issuesFrontiers in Big Data10.3389/fdata.2023.12845116Online publication date: 30-Oct-2023
https://doi.org/10.3389/fdata.2023.1284511
Show More Cited By

Index Terms

Matching Theory-based Recommender Systems in Online Dating
1. Applied computing
  1. Electronic commerce
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

Index terms have been assigned to the content through auto-classification.

Recommendations

Reciprocal recommender system for online dating
RecSys '10: Proceedings of the fourth ACM conference on Recommender systems

Reciprocal recommender is a class of recommender systems that is important for tasks where people are both the subject and the object of the recommendation; one such task is online dating. We have implemented RECON, a reciprocal recommender for online ...
Online dating recommender systems: the split-complex number approach
RSWeb '12: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web

A typical recommender setting is based on two kinds of relations: similarity between users (or between objects) and the taste of users towards certain objects. In environments such as online dating websites, these two relations are difficult to separate, ...
A contextual-bandit approach for multifaceted reciprocal recommendations in online dating
Abstract
Recommender Systems (RS) provide an effective way to deal with the problem of information overload by suggesting relevant items to users that the users may prefer. However, many online social platforms such as online dating and online recruitment ...

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RecSys '22: Proceedings of the 16th ACM Conference on Recommender Systems

September 2022

743 pages

ISBN:9781450392785

DOI:10.1145/3523227

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: 13 September 2022

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RecSys '22: Sixteenth ACM Conference on Recommender Systems

September 18 - 23, 2022

WA, Seattle, USA

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Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Tomita YYokoyama T(2024)Fair Reciprocal Recommendation in Matching MarketsProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688130(209-218)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688130
Yang CDai SHou YZhao WXu JSong YZhu HBaeza-Yates RBonchi F(2024)Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and MethodProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671734(3714-3723)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671734
Felfernig AWundara MTran TPolat-Erdeniz SLubos SEl Mansi MGarber DLe V(2023)Recommender systems for sustainability: overview and research issuesFrontiers in Big Data10.3389/fdata.2023.12845116Online publication date: 30-Oct-2023
https://doi.org/10.3389/fdata.2023.1284511
Tomita YTogashi RHashizume YOhsaka N(2023)Fast and Examination-agnostic Reciprocal Recommendation in Matching MarketsProceedings of the 17th ACM Conference on Recommender Systems10.1145/3604915.3608774(12-23)Online publication date: 14-Sep-2023
https://dl.acm.org/doi/10.1145/3604915.3608774

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Recommendations

Reciprocal recommender system for online dating

Online dating recommender systems: the split-complex number approach

A contextual-bandit approach for multifaceted reciprocal recommendations in online dating

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