会议信息

NOBIDS 2017: Norwegian Big Data Symposium

请登录查看会议网址
免费注册：查看官网链接、跟踪截稿日期，并接收邮件提醒。
注册 登录
嵌入截止倒计时徽章
NOBIDS
用 API 获取这条数据
搜索与榜单列表完全无需凭证；本页的完整详情需要一把免费 API 密钥。详见开发者接入页。
截稿日期:
2017-10-17 Extended
通知日期:
2017-10-27
会议日期:
2017-11-14
会议地点:
Trondheim, Norway
届数:
3
浏览: 15084   关注: 0   参加: 0

会伴指数 (CP-I)

39.5 / 100
全站第 5,153 名 / 共 5,682 个会议 · 前 91%

数据挖掘与数据库 第 311 / 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%)
37
社区关注 (10%)
8
资料公开度 (15%)
25

用到的输入: 有据可查的届次：3 · 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 2026-09-19

征稿

NOBIDS 2017 (Norwegian Big Data Symposium) is an academic conference held in Trondheim, Norway on 2017-11-14. The paper submission deadline is 2017-10-17 (extended). Acceptance notifications are sent on 2017-10-27.

The 3rd Norwegian Big Data Symposium - NOBIDS 2017 welcomes the submission of original research and application papers dealing with all aspects of Big Data and also the speacial theme "Fake News". The impact of Big Data and large-scale data infrastructures is now visible in science, business, government and civil society. Companies store more data than anyone could imagine just a few years back, and the proliferation of open linked data has made it possible to share well-defined data across organizational and geographical boundaries. Big data and data analytics are rapidly expanding research areas that are of great importance to both industry and academia. The focus is on scalable techniques for intelligent data production, collection, classification, storing, integration, analysis and visualization. Big Data is multi-disciplinary of nature and is closely linked to industrial innovation and value creation. The 3rd Norwegian Big Data Symposium (NOBIDS) focuses on Big Data applications and Big Data research from all disciplines. This year NOBIDS has a special focus on fake news. As the term “fake news” became popular within the last years, it is a growing problem to distinguish the real news within the great churn of online news. The effect of social media both as a source of news and the media for spreading the existing news cannot be underestimated. Recently, detection of fake news is mostly done by the manual work of professional journalists while there is also a lot of research going on towards the automatic detection of fake news. Worldwide efforts to professionally and easily spot the fake news, brings the journalists and computer scientists together. NOBIDS 2017 aims to bring researchers and industry practitioners together to exchange ideas, establish collaborations and share experiences within the special theme of fake news. NOBIDS 2017 will be held in conjunction with the NxtMedia Conference in Trondheim. Topics of Interest Topics of interests for the research track of NOBIDS 2017 include but are not limited to: Fake news detection Deception and click-bait detection News classification Detection of trusted news sources News verification Industrial applications of big data and data analytics Handling Big data V's: Volume, Velocity, Variety and Veracity Big data management and life cycle support Big data systems and architectures New programming models and platforms for big data computing Cloud/grid/stream computing for big data Big data on mobile platforms Large-scale semantics and open linked data Big data analytics Big data and AI/machine learning and cognitive computing Big data and Natural Language Processing Big data and High Performance Computing Large-scale recommender systems and personalization News recommender systems and news analytics News summarization, classification and sentiment analysis User experience and visualization of big data User intelligence and user profiling Social media systems Big data anonymisation, privacy and security Data driven innovation Combining open and protected data Business models for big data Legal aspects of open and protected data Evaluation of big data applications Big data benchmarking
由 Dou Sun 最后更新于

相关会议

CCFICORECP-I简称全称截稿日期会议日期
39.8Big DataInternational Conference on Big Data2014-04-302014-08-04
AA*92.4SIGIRInternational Conference on Research and Development in Information Retrieval2026-01-152026-07-20
AA*97.7AAAIAAAI Conference on Artificial Intelligence2026-07-212027-02-16
AA*91.2CVPRIEEE Conference on Computer Vision and Pattern Recognition2025-11-062026-06-03
BA*89.7ICRAInternational Conference on Robotics and Automation2026-09-152027-05-24
BA*94.1IJCAIInternational Joint Conference on Artificial Intelligence2026-01-312026-08-15
AA*89.3STOCACM Symposium on Theory of Computing2025-11-042026-06-22
C87.3ICCInternational Conference on Communications2026-10-022027-05-30
CB62.6IJCNNInternational Joint Conference on Neural Networks2027-01-312027-06-14
B91.2ICASSPInternational Conference on Acoustics, Speech and Signal Processing2026-09-162027-05-16

相关期刊

CCF全称影响因子出版商ISSN
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
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203

评论 0

暂无评论。

请登录后发表评论