FinRec: The 3rd International Workshop on Personalization & Recommender Systems in Financial Services

Toine Bogers, Cataldo Musto, David Wang, Alexander Felfernig, Simone Borg Bruun, Giovanni Semeraro, Yong Zheng

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Abstract

The FinRec workshop series offers a central forum for the study and discussion of the domain-specific aspects, challenges, and opportunities of RecSys and other related technologies in the financial services domain. Six years after the second edition of the workshop, the recent advances in the area of personalization and recommendation in financial services fostered the need for a new workshop aiming at bringing together researchers and practitioners working in financial services-related areas. Accordingly, the third edition of the event aims to: (1) understand and discuss open research challenges, (2) provide an overview of existing technologies using recommender systems in the financial services domain, and (3) provide an interactive platform for information exchange between industry and academia.

Original languageEnglish
Title of host publicationRecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems
Number of pages3
PublisherAssociation for Computing Machinery
Publication date12 Sept 2022
Pages688-690
ISBN (Electronic)9781450392785
DOIs
Publication statusPublished - 12 Sept 2022
Event16th ACM Conference on Recommender Systems, RecSys 2022 - Seattle, United States
Duration: 18 Sept 202223 Sept 2022

Conference

Conference16th ACM Conference on Recommender Systems, RecSys 2022
Country/TerritoryUnited States
CitySeattle
Period18/09/202223/09/2022
SponsorACM Special Interest Group on Artificial Intelligence (SIGAI), ACM Special Interest Group on Computer-Human Interaction (SIGCHI), ACM Special Interest Group on Hypertext, Hypermedia, and Web (SIGWEB), Special Interest Group on Information Retrieval (ACM SIGIR), ACM Special Interest Group on Knowledge Discovery in Data (SIGKDD)
SeriesRecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems

Bibliographical note

Publisher Copyright:
© 2022 Owner/Author.

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(s).
RecSys ’22, September 18–23, 2022, Seattle, WA, USA

Keywords

  • financial services
  • joint optimization
  • personalization
  • recommender systems
  • stakeholders

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