Información de la conferencia

DSS 2026: IEEE International Conference on Data Science and Systems

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Día de Entrega:
2026-07-15 Cerrado
Fecha de Notificación:
2026-09-10
Fecha de conferencia:
2026-10-29
Ubicación:
Luoyang, China
Ediciones:
Vistas: 33455   Seguidores: 25   Asistentes: 5
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Índice Conference Partner (CP-I)

54,3 / 100
Puesto n.º 970 de 5.771 congresos · 17% superior

N.º 47 de 340 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%)
47
Integridad del registro público (15%)
55

Datos utilizados: Ediciones documentadas: 12 · Investigadores que lo siguen aquí: 25 · Investigadores que abrieron esta página en los últimos 24 meses: 7

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 1.2 · Calculado el 2026-11-08

Solicitud de Artículos

DSS 2026 (IEEE International Conference on Data Science and Systems) is an academic conference held in Luoyang, China on 2026-10-29. The paper submission deadline is 2026-07-15. Acceptance notifications are sent on 2026-09-10.

As an interdisciplinary area, Data Science draws scientific inquiry from a broad range of subject areas such as statistics, mathematics, computer science, machine learning, optimization, signal processing, information retrieval, databases, cloud computing, computer vision, natural language processing and etc. Data Science is on the essence of deriving valuable insights from data. It is emerging to meet the challenges of processing very large datasets, i.e. Big Data, with the explosion of new data continuously generated from various channels such as smart devices, web, mobile and social media. Data systems are posing many challenges in exploiting parallelism of current and upcoming computer architectures. Data volumes of applications in the fields of sciences and engineering, finance, media, online information resources, etc. are expected to double every two years over the next decade and further. With this continuing data explosion, it is necessary to store and process data efficiently by utilizing enormous computing power. The importance of data intensive systems has been raised and will continue to be the foremost fields of research. This raise brings up many research issues, in forms of capturing and accessing data effectively and fast, processing it while still achieving high performance and high throughput, and storing it efficiently for future use. Innovative programming models, high performance scalable computing platforms, efficient storage systems and expression of data requirements are at immediate need. DSS (Data Science and Systems) was created to provide a prime international forum for researchers, industry practitioners and domain experts to exchange the latest advances in Data Science and Data Systems as well as their synergy. IEEE DSS-2026 will be held in Luoyang, China, a historic city renowned for its rich cultural heritage and as one of the ancient capitals of China. The city features world-famous landmarks such as the Longmen Grottoes and the White Horse Temple, offering an inspiring environment that blends tradition with modern innovation. Prospective authors are invited to submit their papers to DSS-2026. Accepted papers will be submitted for inclusion into IEEE Xplore, subject to meeting IEEE Xplore’s scope and quality requirements. Authors of selected best papers will be invited to extend their work for special issues of prestigious journals planned in conjunction with the conference. Topics of interest include, but are not limited to: Track 1: Data Science Foundational theories of data science Data classification and taxonomy Data metrics and metrology Data analytics Social network analysis and mining Security, privacy, and trust in data Track 2: Data Processing Technology Data representation and processing Machine learning and deep learning Graph neural networks Semi-supervised and unsupervised learning Statistical, mathematical, and probabilistic modeling and theories Information retrieval Data visualization Track 3: Data Systems Storage and file systems High-performance access toolkits Compiler and runtime support Real-time data-intensive systems Multi-/many-core platforms Big data and cloud computing Track 4: Data Applications Business and financial applications Industrial data applications Bioinformatics applications Healthcare and medical services Applications in soil and water HPC systems for data applications Future data applications
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