会议信息

Smart Data 2016: IEEE International Conference on Smart Data

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Smart Data
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截稿日期:
2016-09-30
通知日期:
2016-10-31
会议日期:
2016-12-15
会议地点:
Chengdu, China
浏览: 14466   关注: 3   参加: 2

会伴指数 (CP-I)

43.4 / 100
全站第 3,608 名 / 共 5,693 个会议 · 前 64%
证据有限：这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里，也没有录用率数据，因此分数的大部分回落到了中性基准。
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%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
22
资料公开度 (15%)
25

用到的输入: 在会伴关注它的研究者：3 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 25% —— 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

Smart Data 2016 (IEEE International Conference on Smart Data) is an academic conference held in Chengdu, China on 2016-12-15. The paper submission deadline is 2016-09-30. Acceptance notifications are sent on 2016-10-31.

Smart Data aims to filter out the noise and hold the valuable data, which can be effectively used by enterprises and governments for planning, operation, monitoring, control, and intelligent decision making. Although unprecedentedly large amount of sensory data can be collected with the advancement of the cyber-physical-social systems recently. However, having lots of data is not enough. The key is to explore how Big Data can become Smart Data. Advanced Big Data modeling and analytics are indispensable for discovering the underlying structure from retrieved data in order to acquire Smart Data. Computational Intelligence, a set of nature-inspired computational methodologies and approaches, has advanced in the past decades. A large number of Computational Intelligent technologies such as artificial neural networks, evolutionary computation and fuzzy logic have been developed to address complex real-world problems. The adoption of Computational Intelligence technologies and theories in handling Big Data could offer a number of advantages. Computational Intelligence is considered as an effective tool for harvesting Smart Data from Big Data. The goal of this symposium is to promote community-wide discussion identifying the Computational Intelligence technologies and theories for Big Data. We seek submissions of papers which invent new techniques, introduce new methodologies, propose new research directions and discuss approaches for unsolved issues.Topics of interest include, but are not limited to: Drill Smart Data from Big Data New Techniques in Smart Data Machine learning algorithms over Big Data Deep learning models, architectures and algorithms for Big Data Brain-inspired representations learning of Big Data High performance computing for Big Data learning Security, privacy and trust in Big Data Streaming data learning Intelligent decision making systems for Big Data Prediction methods for Big Data applications Evolutionary computing in Big Data Swarm Intelligence and Big data Handling uncertainty and incompleteness in Big Data Applications of Fuzzy Set theory, Rough Set theory, and Soft Set theory in Big Data Big Data applications
由 Dou Sun 最后更新于

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