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NOBIDS 2017: Norwegian Big Data Symposium

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NOBIDS
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投稿締切日:
2017-10-17 Extended
通知日:
2017-10-27
開催日:
2017-11-14
開催地:
Trondheim, Norway
開催回数:
3
閲覧: 15083   フォロー: 0   参加: 0

会伴インデックス (CP-I)

39.5 / 100
全 5,682 件中 第 5,153 位 · 上位 91%

データマイニング・データベース 分野 337 件中 第 311 位

学術的評価 (35%) データなし — 中立の基準値 50 点として算入 —
投稿の選択性 (20%) データなし — 中立の基準値 50 点として算入 —
開催回数 (20%)
37
コミュニティの注目度 (10%)
8
公開情報の充実度 (15%)
25

使用した入力: 確認できる開催回数：3 · 過去 24 か月にこのページを開いた研究者：2 人

公開情報で不足しているもの: 過去の採択率 (+4.5) · 過去の開催回 (+3.0) · 最優秀論文の記録 (+2.3)
主催者は会議を認証申請したうえで、このページから直接追加できます。スコアは毎晩再計算されます。このスコアを上げるには

信頼度 45% — スコアのうち、中立の基準値ではなく実際に観測されたデータに基づく割合。 このスコアの算出方法 · ランキングを見る · アルゴリズム版 1.1 · 算出日 2026-09-19

論文募集

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
最終更新：Dou Sun（）

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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
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