BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Venue Radar//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:KDD 2027 Calendar
BEGIN:VEVENT
UID:kdd-2027-deadline-abstract@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20270202T115900Z
DTEND:20270202T125900Z
SUMMARY:[Data Mining & Data Science][Machine Learning] KDD 2027 - Abstract 
 submission deadline (estimated)
DESCRIPTION:Conference title: ACM SIGKDD Conference on Knowledge Discovery 
 and Data Mining\nWebsite: https://kdd2027.kdd.org/\nSource URL: https://k
 dd2026.kdd.org/research-track-call-for-papers/\nLocation: San Jose\, Cali
 fornia\, USA\nTopics: Data Mining & Data Science\, Machine Learning\, Tim
 e Series & Sequential Data\, Federated & Distributed Learning\nSize: XL\n
 Submission type: Paper-based / mixed tracks\nConfidence: estimated\nLast 
 checked date: 2026-10-06\nNotes: Official site confirms San Jose\, Aug 1-
 5. The first research-track cycle closed in July 2026. A February 2027 cy
 cle is announced but exact dates are still TBA\; the February abstract/pa
 per dates here are estimated from 2026.\nScope: Knowledge discovery and d
 ata science\, centered on extracting useful structure from large\, hetero
 geneous data. Characteristic areas include clustering\, structured and re
 lational learning\, graph and text mining\, recommender systems\, scalabl
 e data analysis\, and responsible data use. Generative AI is relevant whe
 n it advances data science\, not simply because a paper uses an LLM.\nAdd
 itional topics: Deep Representation Learning\, Natural Language Processin
 g & LLMs\, Explainability & Interpretability\, Privacy-preserving ML\, ML
  Systems & Infrastructure\nScope sources (2027): https://kdd2027.kdd.org/
 research-track-call-for-papers/\nScope last checked: 2026-10-07
URL:https://kdd2026.kdd.org/research-track-call-for-papers/
END:VEVENT
BEGIN:VEVENT
UID:kdd-2027-deadline-full-paper@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20270209T115900Z
DTEND:20270209T125900Z
SUMMARY:[Data Mining & Data Science][Machine Learning] KDD 2027 - Paper sub
 mission deadline (estimated)
DESCRIPTION:Conference title: ACM SIGKDD Conference on Knowledge Discovery 
 and Data Mining\nWebsite: https://kdd2027.kdd.org/\nSource URL: https://k
 dd2026.kdd.org/research-track-call-for-papers/\nLocation: San Jose\, Cali
 fornia\, USA\nTopics: Data Mining & Data Science\, Machine Learning\, Tim
 e Series & Sequential Data\, Federated & Distributed Learning\nSize: XL\n
 Submission type: Paper-based / mixed tracks\nConfidence: estimated\nLast 
 checked date: 2026-10-06\nNotes: Official site confirms San Jose\, Aug 1-
 5. The first research-track cycle closed in July 2026. A February 2027 cy
 cle is announced but exact dates are still TBA\; the February abstract/pa
 per dates here are estimated from 2026.\nScope: Knowledge discovery and d
 ata science\, centered on extracting useful structure from large\, hetero
 geneous data. Characteristic areas include clustering\, structured and re
 lational learning\, graph and text mining\, recommender systems\, scalabl
 e data analysis\, and responsible data use. Generative AI is relevant whe
 n it advances data science\, not simply because a paper uses an LLM.\nAdd
 itional topics: Deep Representation Learning\, Natural Language Processin
 g & LLMs\, Explainability & Interpretability\, Privacy-preserving ML\, ML
  Systems & Infrastructure\nScope sources (2027): https://kdd2027.kdd.org/
 research-track-call-for-papers/\nScope last checked: 2026-10-07
URL:https://kdd2026.kdd.org/research-track-call-for-papers/
END:VEVENT
BEGIN:VEVENT
UID:kdd-2027-conference@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270801
DTEND;VALUE=DATE:20270806
SUMMARY:[Data Mining & Data Science][Machine Learning] KDD 2027 - Conferenc
 e
DESCRIPTION:Conference title: ACM SIGKDD Conference on Knowledge Discovery 
 and Data Mining\nWebsite: https://kdd2027.kdd.org/\nSource URL: https://k
 dd2027.kdd.org/\nLocation: San Jose\, California\, USA\nTopics: Data Mini
 ng & Data Science\, Machine Learning\, Time Series & Sequential Data\, Fe
 derated & Distributed Learning\nSize: XL\nSubmission type: Paper-based / 
 mixed tracks\nConfidence: confirmed\nLast checked date: 2026-10-06\nNotes
 : Official site confirms San Jose\, Aug 1-5. The first research-track cyc
 le closed in July 2026. A February 2027 cycle is announced but exact date
 s are still TBA\; the February abstract/paper dates here are estimated fr
 om 2026.\nScope: Knowledge discovery and data science\, centered on extra
 cting useful structure from large\, heterogeneous data. Characteristic ar
 eas include clustering\, structured and relational learning\, graph and t
 ext mining\, recommender systems\, scalable data analysis\, and responsib
 le data use. Generative AI is relevant when it advances data science\, no
 t simply because a paper uses an LLM.\nAdditional topics: Deep Representa
 tion Learning\, Natural Language Processing & LLMs\, Explainability & Int
 erpretability\, Privacy-preserving ML\, ML Systems & Infrastructure\nScop
 e sources (2027): https://kdd2027.kdd.org/research-track-call-for-papers/
 \nScope last checked: 2026-10-07
URL:https://kdd2027.kdd.org/
LOCATION:San Jose\, California\, USA
END:VEVENT
END:VCALENDAR