会议信息

DaWaK 2026: International Conference on Big Data Analytics and Knowledge Discovery

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DaWaK
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截稿日期:
2026-03-15
通知日期:
2026-05-15
会议日期:
2026-08-11
会议地点:
Graz, Austria
届数:
28
ICORE: B   QUALIS: B1   浏览: 46550   关注: 6   参加: 0

会伴指数 (CP-I)

63.8 / 100
全站第 480 名 / 共 5,693 个会议 · 前 9%

数据挖掘与数据库 第 23 / 337

学术认可 (35%)
78
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
91
社区关注 (10%)
31
资料公开度 (15%)
35

用到的输入: 收录等级：ICORE B, QUALIS B1 · 有据可查的届次：28 · 在会伴关注它的研究者：6 人 · 过去 24 个月打开过本页的研究者：4 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 80% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-03

征稿

DaWaK 2026 (International Conference on Big Data Analytics and Knowledge Discovery) is a ICORE B / QUALIS B1 conference held in Graz, Austria on 2026-08-11. The paper submission deadline is 2026-03-15. Acceptance notifications are sent on 2026-05-15.

Scope DaWaK conference is a high-quality forum for researchers, practitioners and developers in the field of Big Data Analytics, in a broad sense. The objective is to explore, disseminate and exchange knowledge in this field through scientific and industry talks. The conference covers all aspects of DAWAK research and practice, including data lakes, database design (data warehouse design, ER modelling), big data management (tables + text + files), query languages (SQL and beyond), parallel systems technology (Spark, MapReduce, HDFS), theoretical foundations and applications, text and data mining techniques, and deep learning. Topics of Interest The conference will bring together active researchers from the database systems, cloud computing, programming languages and data science communities worldwide. Main topics include: Theoretical models for data storage Integration of databases and neural networks Conceptual model foundations for big data Parallel and scalable data processing Distributed and parallel system architectures Query processing and optimization Semantics for big data Data fabric and data lake architectures Data Pre-processing and data cleaning Polystore and multistore architectures SQL alternatives: NoSQL, NewSQL, JSON Cloud infrastructure; containers, virtualization Metadata for big data frameworks Big data storage and indexing Mobile applications Large-scale AI/ML for Multimodal dataa Data Science workflows Analytics on Large Graphs Large-scale unstructured, semi-structured data Data streams: networking and sensor data Trustworthy AI on Data Lakes, Data Grid and Data Fabric Deep learning on large data sets
由 Dou Sun 最后更新于

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CCF全称影响因子出版商ISSN
Materials DiscoveryElsevier2352-9245
BData Mining and Knowledge Discovery4.3Springer1384-5810
Journal of Big Data6.4Springer2196-1115
Big Data Research4.2Elsevier2214-5796
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312

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