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BDC 2015: IEEE/ACM International Symposium on Big Data Computing

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회원가입 로그인
투고 마감일:
2015-07-03 마감됨
통보일:
2015-08-21
개최일:
2015-12-07
개최지:
Limassol, Cyprus
개최 횟수:
2
조회: 16341   팔로우: 1   참가: 0
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BDC
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회반 지수 (CP-I)

38.7 / 100
전체 5,705개 중 5,368위 · 상위 95%

데이터 마이닝·데이터베이스 분야 336개 중 320위

학술적 인정 (35%) 데이터 없음 — 중립 기준값 50점으로 계산 —
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
30
커뮤니티 관심도 (10%)
15
공개 자료 충실도 (15%)
25

사용한 입력: 확인되는 개최 횟수: 2 · 회반에서 팔로우 중인 연구자: 1명 · 지난 24개월 동안 이 페이지를 연 연구자: 2명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 역대 회차 (+3.0) · 최우수 논문 기록 (+2.3)
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신뢰도 45% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.2 · 산출일 2026-10-16

논문 모집

BDC 2015 (IEEE/ACM International Symposium on Big Data Computing) is an academic conference held in Limassol, Cyprus on 2015-12-07. The paper submission deadline is 2015-07-03. Acceptance notifications are sent on 2015-08-21.

Rapid advances in digital sensors, networks, storage, and computation along with their availability at low cost is leading to the creation of huge collections of data -- dubbed as Big Data. This data has the potential for enabling new insights that can change the way business, science, and governments deliver services to their consumers and can impact society as a whole. This has led to the emergence of the Big Data Computing paradigm focusing on sensing, collection, storage, management and analysis of data from variety of sources to enable new value and insights. To realize the full potential of Big Data Computing, we need to address several challenges and develop suitable conceptual and technological solutions for dealing them. These include life-cycle management of data, large-scale storage, flexible processing infrastructure, data modelling, scalable machine learning and data analysis algorithms, techniques for sampling and making trade-off between data processing time and accuracy, and dealing with privacy and ethical issues involved in data sensing, storage, processing, and actions. The International Symposium on Big Data Computing (BDC) 2015 -- held in conjunction with 8th IEEE/ACM International Conference on Utility and Cloud Computing (UCC) 2015, December 7-10, 2015, St. Raphael Resort, Limassol, Cyprus, aims at bringing together international researchers, developers, policy makers, and users and to provide an international forum to present leading research activities, technical solutions, and results on a broad range of topics related to Big Data Computing paradigms, platforms and their applications. The conference features keynotes, technical presentations, posters, and workshops. Topics Topics of interest include, but are not limited to: I. Big Data Science • Analytics • Algorithms for Big Data • Energy-efficient Algorithms • Big Data Search • Big Data Acquisition, Integration, Cleaning, and Best Practices • Visualization of Big Data II. Big Data Infrastructures and Platforms • Programming Systems • Cyber-Infrastructure • Performance evaluation • Fault tolerance and reliability • I/O and Data management • Storage Systems (including file systems, NoSQL, and RDBMS) • Resource management • Many-Task Computing • Many-core computing and accelerators III. Big Data Security and Policy • Management Policies • Data Privacy • Data Security • Big Data Archival and Preservation • Big Data Provenance IV. Big Data Applications • Scientific application cases studies on Cloud infrastructure • Big Data Applications at Scale • Experience Papers with Big Data Application Deployments • Data streaming applications • Big Data in Social Networks • Healthcare Applications • Enterprise Applications
최종 수정: Dou Sun ()

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관련 저널

CCF정식 명칭영향력 지수출판사ISSN
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

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