会议信息

BigDataSE 2025: International Conference on Big Data Science and Engineering

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截稿日期:
2025-08-01 已截稿
通知日期:
2025-10-01
会议日期:
2025-11-14
会议地点:
Guiyang, China
届数:
19
浏览: 29704   关注: 15   参加: 0
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会伴指数 (CP-I)

52.4 / 100
全站第 1,189 名 / 共 5,696 个会议 · 前 21%

数据挖掘与数据库 第 59 / 336

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
81
社区关注 (10%)
35
资料公开度 (15%)
35

用到的输入: 有据可查的届次：19 · 在会伴关注它的研究者：15 人 · 过去 24 个月打开过本页的研究者：2 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 45% —— 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 1.2 · 算于 2026-10-15

征稿

BigDataSE 2025 (International Conference on Big Data Science and Engineering) is an academic conference held in Guiyang, China on 2025-11-14. The paper submission deadline is 2025-08-01. Acceptance notifications are sent on 2025-10-01.

Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud/stream computing platforms, and high performance/parallel computing platforms. The 19th IEEE International Conference on Big Data Science and Engineering (BigDataSE-2025) is going to provide a prime international forum for researchers, industry practitioners and environment experts to exchange the latest fundamental advances in the state of the art and practice of Big Data and broadly related areas. The goal of this conference is to promote community-wide discussion for identifying advanced applications, technologies and theories for big data. We seek submissions of papers that invent novel techniques, investigate new applications, introduce advanced methodologies, propose promising research directions and discuss approaches for unsolved issues. BigDataSE-2025 will be hosted in Guiyang, China. Guiyang, a vibrant mountain city embraced by lush forests and karst landscapes, offers an excellent venue for the conference while inviting exploration of its unique attractions. Visitors can discover renowned sites such as the ancient town of Qingyan, the serene Qianling Mountain Park, and the breathtaking natural wonders of Huaxi National Urban Wetland Park and Tianhe Tan Karst Geological Park. Prospective authors are invited to submit their papers to BigDataSE-2025. Accepted papers will be submitted for possible inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements. The authors of selected best papers will be invited post conference to extend their contributions for special issues of prestigious journals to be planned in conjunction with the conference. Topics Topics of interest include, but are not limited to: •Novel theories, computational models, and algorithms of Big Data •Big Data standards •Big Data search and mining •Big Data learning and analytics •Big Data infrastructure, high performance/parallel computing platforms •Big Data visualization •Big Data curation and management •Big Data semantics, scientific discovery and intelligence •Big Data performance analysis and large-scale deployment •Security, privacy, trust, and legal issues about Big Data •Big Data vs Big Business and Big Industry •Large data stream processing •Large incremental datasets •Distributed and federated datasets •NoSQL data stores and Big Data compression •Big Data placement, scheduling, and optimization •Distributed file systems for Big Data •MapReduce for Big Data processing, resource scheduling and SLA •Performance characterization, evaluation and optimization •Simulation and debugging systems and tools for MapReduce and Big Data •Volume, Velocity, Variety, Value and Veracity of Big Data •Multi-source Big Data processing and integration •Storage and computation management of Big Data •Large-scale Big Data workflow management •Big Data sensing and crowdsourcing •Sensor network, social network and Big Data •Big Data ecosystem •Foundation models and Big Data •Big Data applications
由 Dou Sun 最后更新于

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