Información de la conferencia

DTMN 2026: International Conference on Data Mining

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DTMN
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Día de Entrega:
2026-09-26
Fecha de Notificación:
2026-10-03
Fecha de conferencia:
2026-10-17
Ubicación:
Sydney, Australia
Ediciones:
Vistas: 17252   Seguidores: 3   Asistentes: 0

Índice Conference Partner (CP-I)

51,9 / 100
Puesto n.º 1.227 de 5.693 congresos · 22% superior

N.º 62 de 337 en Minería de datos y bases de datos

Reconocimiento académico (35%) Sin datos: se puntúa con la línea base neutra de 50 —
Selectividad en la revisión (20%) Sin datos: se puntúa con la línea base neutra de 50 —
Ediciones celebradas (20%)
69
Atención de la comunidad (10%)
24
Integridad del registro público (15%)
55

Datos utilizados: Ediciones documentadas: 12 · Investigadores que lo siguen aquí: 3 · Investigadores que abrieron esta página en los últimos 24 meses: 3

Falta en el registro público: Tasas de aceptación históricas (+4,5) · Premios al mejor artículo (+2,3)
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Confianza 45 %: la parte de la puntuación respaldada por datos observados y no por la línea base neutra. Cómo se calcula esta puntuación · Ver la clasificación · Versión del algoritmo 1.1 · Calculado el 2026-10-05

Solicitud de Artículos

DTMN 2026 (International Conference on Data Mining) is an academic conference held in Sydney, Australia on 2026-10-17. The paper submission deadline is 2026-09-26. Acceptance notifications are sent on 2026-10-03.

Scope & Topics 12th International Conference on Data Mining (DTMN 2026) provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum. Authors are solicited to contribute to the conference by submitting articles that illustrate research results projects surveying works and industrial experiences that describe significant advances in Data mining and Applications. Authors are solicited to contribute to the conference by submitting articles that illustrate research results projects surveying works and industrial experiences. All submissions must describe original research not published or currently under review for another conference or journal. Topics of interest include, but are not limited to, the following: · Foundations of Data Mining · Large Scale, Distributed and Cloud Native Data Mining · Federated, On‑Device and Privacy Preserving Mining · Mining Text, Web, Graph, Social and Semi Structured Data · Spatio‑Temporal, Streaming and Real Time Mining · Multimedia and Multimodal Data Mining · Graph Mining, Network Science and Knowledge Graphs · Deep Learning, Representation Learning and Feature Engineering · Self‑Supervised, Contrastive and Semi Supervised Mining · Active Learning and Reinforcement Learning for Mining · Mining Foundation Model Outputs and LLM Behaviors · Mining Multimodal Foundation Models · LLM‑Driven and Autonomous Data Mining Pipelines · Agentic AI and Multi Agent Mining Systems · Generative AI for Data Mining · Causal Discovery and Causal Data Mining · Knowledge Discovery, Pattern Mining and Frequent Structures · Scientific ML, Symbolic Regression and Scientific Data Mining · Anomaly Detection, Outlier Analysis and Rare Event Mining · Personalization, Recommendation and User Modeling · Search, Ranking and Information Retrieval Mining · Security, Privacy, Fraud and Threat Intelligence Mining · Adversarial Data Mining and Robustness · IoT, Sensor Fusion and Cyber Physical Systems Mining · Autonomous Systems and Vehicle Data Mining · Edge‑Native and TinyML Driven Data Mining · Healthcare, Biological and Medical Data Mining · Climate, Environmental and Sustainability Data Mining · Financial, Economic and Business Data Mining · Social Media, Social Networks and Human Behavior Mining · Human Centric and Societal Scale Data Mining · Logs, Telemetry, Observability and AIOps Mining · Synthetic Data Generation and Augmentation · AutoML, Meta Learning and Automated Mining Pipelines · Explainable and Interpretable Data Mining · Fairness, Ethics, Bias and Responsible Data Mining · Safety Critical Data Mining and Risk Sensitive Analytics · Data Governance, Lineage and Quality Mining
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