FinRec: The 3rd International Workshop on Personalization & Recommender Systems in Financial Services
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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 language | English |
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Title of host publication | RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems |
Number of pages | 3 |
Publisher | Association for Computing Machinery, Inc. |
Publication date | 2022 |
Pages | 688-690 |
ISBN (Electronic) | 9781450392785 |
DOIs | |
Publication status | Published - 2022 |
Event | 16th ACM Conference on Recommender Systems, RecSys 2022 - Seattle, United States Duration: 18 Sep 2022 → 23 Sep 2022 |
Conference
Conference | 16th ACM Conference on Recommender Systems, RecSys 2022 |
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Land | United States |
By | Seattle |
Periode | 18/09/2022 → 23/09/2022 |
Sponsor | ACM 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), ACM Special Interest Group on Information Retrieval (SIGIR), ACM Special Interest Group on Knowledge Discovery in Data (SIGKDD) |
Bibliographical note
Publisher Copyright:
© 2022 Owner/Author.
- financial services, joint optimization, personalization, recommender systems, stakeholders
Research areas
ID: 344981235