会議情報

BIDMA 2017: International Symposium on Big Data Management and Analytics

会議のウェブサイトを表示するにはログインしてください
無料登録で公式サイトの閲覧、締切のトラッキング、メールリマインダーが利用できます。
新規登録 ログイン
投稿締切日:
2017-02-28 延長
通知日:
2017-03-20
開催日:
2017-04-17
開催地:
Calgary, Alberta, Canada
閲覧: 15491   フォロー: 1   参加: 0
このページに誤りがありますか？お知らせください
締切カウントダウンバッジを埋め込む
BIDMA
このデータを API で取得
検索とランキング一覧は資格情報なしで利用できます。このページの詳細データには無料の API キーが必要です。詳しくは開発者向けガイドをご覧ください。

会伴インデックス (CP-I)

42.7 / 100
全 5,693 件中 第 3,863 位 · 上位 68%

データマイニング・データベース 分野 336 件中 第 225 位

根拠が限られています：この会議は CCF / ICORE / QUALIS のいずれにも収録されておらず、採択率のデータもないため、スコアの大部分は中立の基準値に戻ります。
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%) データなし — 中立の基準値 50 点として算入 —
コミュニティの注目度 (10%)
15
公開情報の充実度 (15%)
25

使用した入力: 会伴でフォローしている研究者：1 人 · 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 25% — 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 2026-10-08

論文募集

BIDMA 2017 (International Symposium on Big Data Management and Analytics) is an academic conference held in Calgary, Alberta, Canada on 2017-04-17. The paper submission deadline is 2017-02-28 (extended). Acceptance notifications are sent on 2017-03-20.

BIDMA organizing committee invites you to participate in the first edition of Big Data Management and Analytics symposium proceedings, to be held on April 17-18, 2017, Calgary, Canada. The theme topic of the conference will all revolve not only around technology aspect of Big Data management but also business and application aspect of different services (web-based services, cloud-based services, business services, mobile services, and Big Data services). Tracks Papers can be submitted to one of the following tracks: a) Academic Track The objective of the Academic Track at BIDMA 2017 is to provide a strong basis for collaboration among researchers to conduct research in the field of data management and data analytics. BIDMA 2017 strives to offer papers which describe various tools, techniques and methodologies which explore the contemporary challenges with data management, processing and analytics. b) Industry Track The objective of the Industry Track at BIDMA 2017 is to establish dialog and encourage collaboration among practitioners and researchers in the data analytics community. The industry track papers will address the application of data management and data analytics to a specific problem domain. c) Thesis Track This track is intended for students at any stage of their PhD work. The selected students will be requested to present their work in a special session of the BIDMA 2017 Symposium. These Students will be given an opportunity to get feedback and advice on how to improve their PhD thesis research. Topics Major topics include but not limited to the following: Big Data Models, Algorithms and Architecture Foundational Models for Big Data Algorithms and Programming Techniques for Big Data Processing Big Data Analytics and Metrics Representation Formats for Multimedia Big Data Cloud Computing Techniques for Big Data Big Data as a Service Big Data Open Platforms Algorithms and Systems for Big Data Search Machine learning based on Big Data Visualization Analytics for Big Data Big Data Management and Analytics Big Data Persistence and Preservation Big Data Quality and Provenance Control Management Issues of Social Network Big Data Privacy Preserving Big Data Analytics Security Applications of Big Data Anomaly Detection in Very Large Scale Systems Collaborative Threat Detection using Big Data Analytics Big Data Encryption Big Data for Enterprise, Government and Society Big Data Economics Real-life Case Studies of Value Creation through Big Data Analytics Big Data for Business Model Innovation Big Data Toolkits Big Data in Business Performance Management Scientific Applications of Big Data Large-scale Social Media and Recommendation Systems Experiences with Big Data Project Deployments Big Data in Enterprise Management Models and Practices Big Data in Government Management Models and Practices Big Data in Smart Planet Solutions Big Data for Enterprise Transformation Big Data in Education Curriculum Development in Big Data Pedagogical Methods in Big Data Analysis Data Science Curricula Development and Challenges in Data-Oriented Education Building Repositories to Support Education Best Paper Award BIDMA will be presenting a Best Paper award. The best paper will be selected by separate committee and will be the one that reports the most novel and promising research work that has a high potential impact in the real world. The prize consists of an official certificate and reward in cash.
最終更新：Dou Sun（）

関連会議

CCFICORECP-I略称正式名称投稿締切開催日
39.8Big DataInternational Conference on Big Data2014-04-302014-08-04
43.4IEEE Big Data ServiceIEEE International Conference On Big Data Service and Applications2018-11-302019-04-04
AA*92.6SIGIRInternational Conference on Research and Development in Information Retrieval2026-01-152026-07-20
AA*97.8AAAIAAAI Conference on Artificial Intelligence2026-07-212027-02-16
AA*94.4CVPRIEEE Conference on Computer Vision and Pattern Recognition2026-11-102027-06-20
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*92.6STOCACM Symposium on Theory of Computing2026-11-022027-06-06
C87.5ICCInternational Conference on Communications2026-10-022027-05-30
CB62.8IJCNNInternational Joint Conference on Neural Networks2027-01-312027-06-14

関連ジャーナル

CCF正式名称インパクトファクター出版社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

コメント 0

まだコメントはありません。

コメントするにはログインしてください