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IEEE Big Data Service 2019: IEEE International Conference On Big Data Service and Applications

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IEEE Big Data Service
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截稿日期:
2018-11-30
通知日期:
2019-01-10
会议日期:
2019-04-04
会议地点:
San Francisco, California, USA
届数:
5
浏览: 16552   关注: 5   参加: 2

会伴指数 (CP-I)

43.4 / 100
全站第 3,556 名 / 共 5,682 个会议 · 前 63%

数据挖掘与数据库 第 210 / 337

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%)
48
社区关注 (10%)
26
资料公开度 (15%)
25

用到的输入: 有据可查的届次：5 · 在会伴关注它的研究者：5 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 1.1 · 算于 2026-09-14

征稿

IEEE Big Data Service 2019 (IEEE International Conference On Big Data Service and Applications) is an academic conference held in San Francisco, California, USA on 2019-04-04. The paper submission deadline is 2018-11-30. Acceptance notifications are sent on 2019-01-10.

Big-Data computing and services have received significant attention in recent years. The IEEE BigDataService 2019 aims to provide a forum for researchers and practitioners to exchange innovative ideas, latest research results, and practice experiences and lessons learned. Its major objectives include big-data applications in various domains such as healthcare, business and financing, education and learning, social networks and media, urban and environment, sensors and Internet of things as well as technology aspects of big data computing and services such as computing services and architecture, modeling, data mining and analytics. The conference will be co-located with IEEE SOSE 2019, IEEE MobileCloud 2019 and IEEE DAPPCON 2019. IEEE BigDataService 2019 will consist of main tracks and special tracks. The conference will include 3 International Workshops of Smart City Big Data Analysis, Big Data in Water Resources, Environment, and Hydraulic from Engineering, and Industry Big Data and Signal Processing. Workshop proposal is due 10/15/2018. The conference seeks the submission of high-quality papers limited to 10 pages (IEEE format) in length. All accepted papers will be included in the proceedings. Selected papers will be invited for extension and published in journals (SCI-Index). TOPICS OF INTEREST (INCLUDE BUT NOT LIMITED TO) Big Data Foundations Foundational theoretical or computational models for big data Programming models, theories, and algorithms for big data Standards, protocols, and quality assurance for big data Big Data Platforms and Technologies Innovative, concurrent, and scalable big data platforms Data indexing, cleaning, transformation, and curation technologies Big data processing frameworks and technologies Big data services and application development methods and tools Big data quality evaluation and assurance technologies Big data system reliability and availability Open-source development and technology for big data Big Data as a Service (BDaaS) platform and technologies Big Data Analytics and Services Algorithms and systems for big data search, analytics and visualization Artificial Intelligence for big data and based on big data Visualization analytics for big data Knowledge extraction, discovery, analysis, presentation, and visualization Big Data Applications and Experiences Innovative big data applications and services in industries and domains e.g. healthcare, finance, insurance, transportation, agriculture, education, environment, multi-media, social networks, urban planning, disaster management, security Experiences and case studies of big data applications and services Real-world and large-scale practices of big data Emerging Topics Sensor networks and Internet of Things Networking and protocols Smart City SPECIAL TRACKS Special Track on Real-time Big Data Services and Applications Models, algorithms, and technologies for real-time big data services and applications Experiences, practices and case studies of real-time big data services and applications Special Track on Big Data Security, Privacy and Trust Models, algorithms and technologies for big data security and integrity Practical security and privacy technologies and applications for big data Special Track on Big Data and analytics for Healthcare Models, algorithms, and technologies of big data for healthcare Big data services and applications for healthcare Experiences, practices and case studies of big data technologies for healthcare
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