BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Venue Radar//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:RecSys 2027 Calendar
BEGIN:VEVENT
UID:recsys-2027-deadline-abstract@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20270415T115900Z
DTEND:20270415T125900Z
SUMMARY:[Recommender Systems][Machine Learning] RecSys 2027 - Estimated mai
 n-track abstract deadline (estimated)
DESCRIPTION:Conference title: ACM Conference on Recommender Systems\nWebsit
 e: https://recsys.acm.org/recsys27/\nSource URL: https://recsys.acm.org/r
 ecsys26/call/\nLocation: Honolulu\, Hawaii\, USA\nTopics: Recommender Sys
 tems\, Machine Learning\, Information Retrieval & Search\, Human-AI Inter
 action & Deployment\nSize: L\nSubmission type: Paper-based\nConfidence: e
 stimated\nLast checked date: 2026-10-07\nNotes: 2027 Hawaii meeting is co
 nfirmed. Main-track deadlines are one-year proxies from 2026\; long and s
 hort papers shared the same abstract gate in that edition. Do not infer a
  special twentieth-anniversary track for 2027. Size is an editorial estim
 ate.\nScope: Recommendation and personalization: user-item modeling\, col
 laborative and content-based methods\, sequential and conversational reco
 mmendation\, evaluation\, and deployed recommendation systems. Human and 
 economic impacts matter alongside algorithms. Sequential data is relevant
  specifically through recommendation behavior\; this is not a general for
 ecasting conference.\nAdditional topics: Time Series & Sequential Data\, 
 Natural Language Processing & LLMs\, Fairness & Responsible AI\, Explaina
 bility & Interpretability\nScope sources (2026): https://recsys.acm.org/r
 ecsys26/call/\nScope last checked: 2026-10-07
URL:https://recsys.acm.org/recsys26/call/
END:VEVENT
BEGIN:VEVENT
UID:recsys-2027-deadline-full-paper@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20270422T115900Z
DTEND:20270422T125900Z
SUMMARY:[Recommender Systems][Machine Learning] RecSys 2027 - Estimated mai
 n-track paper deadline (estimated)
DESCRIPTION:Conference title: ACM Conference on Recommender Systems\nWebsit
 e: https://recsys.acm.org/recsys27/\nSource URL: https://recsys.acm.org/r
 ecsys26/call/\nLocation: Honolulu\, Hawaii\, USA\nTopics: Recommender Sys
 tems\, Machine Learning\, Information Retrieval & Search\, Human-AI Inter
 action & Deployment\nSize: L\nSubmission type: Paper-based\nConfidence: e
 stimated\nLast checked date: 2026-10-07\nNotes: 2027 Hawaii meeting is co
 nfirmed. Main-track deadlines are one-year proxies from 2026\; long and s
 hort papers shared the same abstract gate in that edition. Do not infer a
  special twentieth-anniversary track for 2027. Size is an editorial estim
 ate.\nScope: Recommendation and personalization: user-item modeling\, col
 laborative and content-based methods\, sequential and conversational reco
 mmendation\, evaluation\, and deployed recommendation systems. Human and 
 economic impacts matter alongside algorithms. Sequential data is relevant
  specifically through recommendation behavior\; this is not a general for
 ecasting conference.\nAdditional topics: Time Series & Sequential Data\, 
 Natural Language Processing & LLMs\, Fairness & Responsible AI\, Explaina
 bility & Interpretability\nScope sources (2026): https://recsys.acm.org/r
 ecsys26/call/\nScope last checked: 2026-10-07
URL:https://recsys.acm.org/recsys26/call/
END:VEVENT
BEGIN:VEVENT
UID:recsys-2027-conference@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270823
DTEND;VALUE=DATE:20270828
SUMMARY:[Recommender Systems][Machine Learning] RecSys 2027 - Conference
DESCRIPTION:Conference title: ACM Conference on Recommender Systems\nWebsit
 e: https://recsys.acm.org/recsys27/\nSource URL: https://recsys.acm.org/r
 ecsys27/\nLocation: Honolulu\, Hawaii\, USA\nTopics: Recommender Systems\
 , Machine Learning\, Information Retrieval & Search\, Human-AI Interactio
 n & Deployment\nSize: L\nSubmission type: Paper-based\nConfidence: confir
 med\nLast checked date: 2026-10-07\nNotes: 2027 Hawaii meeting is confirm
 ed. Main-track deadlines are one-year proxies from 2026\; long and short 
 papers shared the same abstract gate in that edition. Do not infer a spec
 ial twentieth-anniversary track for 2027. Size is an editorial estimate.\
 nScope: Recommendation and personalization: user-item modeling\, collabor
 ative and content-based methods\, sequential and conversational recommend
 ation\, evaluation\, and deployed recommendation systems. Human and econo
 mic impacts matter alongside algorithms. Sequential data is relevant spec
 ifically through recommendation behavior\; this is not a general forecast
 ing conference.\nAdditional topics: Time Series & Sequential Data\, Natur
 al Language Processing & LLMs\, Fairness & Responsible AI\, Explainabilit
 y & Interpretability\nScope sources (2026): https://recsys.acm.org/recsys
 26/call/\nScope last checked: 2026-10-07
URL:https://recsys.acm.org/recsys27/
LOCATION:Honolulu\, Hawaii\, USA
END:VEVENT
END:VCALENDAR