학회 정보

BigData' 2015: ASE International Conference on Big Data

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회원가입 로그인
투고 마감일:
2015-07-28 마감됨
통보일:
2015-08-21
개최일:
2015-10-07
개최지:
Kaohsiung, Taiwan
개최 횟수:
5
조회: 15445   팔로우: 0   참가: 0
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BigData'
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회반 지수 (CP-I)

41.7 / 100
전체 5,738개 중 4,689위 · 상위 82%

데이터 마이닝·데이터베이스 분야 339개 중 278위

학술적 인정 (35%) 데이터 없음 — 중립 기준값 50점으로 계산 —
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
48
커뮤니티 관심도 (10%)
8
공개 자료 충실도 (15%)
25

사용한 입력: 확인되는 개최 횟수: 5 · 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 2026-10-20

논문 모집

BigData' 2015 (ASE International Conference on Big Data) is an academic conference held in Kaohsiung, Taiwan on 2015-10-07. The paper submission deadline is 2015-07-28 (extended). Acceptance notifications are sent on 2015-08-21.

The ASE International Conference on Big Data aims to bring together academic scientists, researchers and scholars to exchange and share their experiences and research results in Advancing Big Data Science & Engineering (BIGDATA). The phrase “big data” in this solicitation refers to large, diverse, complex, longitudinal, and/or distributed data sets generated from instruments, sensors, Internet transactions, email, video, click streams, and/or all other digital sources available today and in the future. The current focus is to advance the core scientific and technological means of managing, analyzing, visualizing, and extracting useful information from large, diverse, distributed and heterogeneous data sets so as to: accelerate the progress of scientific discovery and innovation; lead to new fields of inquiry that would not otherwise be possible; encourage the development of new data analytic tools and algorithms; facilitate scalable, accessible, and sustainable data infrastructure; increase understanding of human and social processes and interactions; and promote economic growth and improved health and quality of life. The new knowledge, tools, practices, and infrastructures produced will enable breakthrough discoveries and innovation in science, engineering, medicine, commerce, education, and national security. A long-term strategy to address various big data challenges, which include advances in core techniques and technologies; big data infrastructure projects in various science, biomedical research, health and engineering communities; education and workforce development; and a comprehensive integrative program to support collaborations of multi-disciplinary teams and communities to make advances in the complex grand challenge science, biomedical research, and engineering problems of a computational- and data-intensive world. The conferences were held in Washington D.C. in 2012, in Orlando, Florida in 2013, and at Harvard University, Cambridge, MA in 2014. This year is the first time for the conference to be held outside USA. It will be hosted by National University of Kaohsiung, Taiwan from Oct. 7th to 9th, 2015, and held jointly with the Fourth ASE International Conference on Social Informatics. Topics of particular interest include, but are not limited to: Big Data Science: Theories, models, algorithms, benchmarking, curation, and methods for understanding big data Big Data Computing: Infrastructures, tools, programming, architectures, benchmarking, and testing of big data systems using Map/Reduce, Hadoop and others Big Data Mining: Acquisition, representation, indexing, storage, management, processing, pre-processing and post-processing of big data Big Data Analytics: Metrics, frameworks, evaluation, tools, analysis, visualization of big data Big Data Understanding: learning, knowledge discovery, business and consumer intelligence, user behavior, community discovery Big Data Applications: Industrial and scientific applications of big data such as search, recommendations, business intelligence, marketing, social media, good practices and reproducibility. Big Data Privacy and Security: Data privacy enhancing technologies, privacy-preserving computing, risk analysis, modeling, and management, trustworthy computing, access control
최종 수정: Dou Sun ()

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관련 저널

CCF정식 명칭영향력 지수출판사ISSN
BAutomated Software Engineering3.1Springer0928-8910
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

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