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DATA 2027: International Conference on Data Science, Technology and Applications

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투고 마감일:
2027-03-25 164일 남음
통보일:
2027-05-17
개최일:
2027-07-19
개최지:
Rome, Italy
개최 횟수:
캘린더에 추가: Google 캘린더 · Outlook / Apple (.ics)
ICORE: C   조회: 18709   팔로우: 5   참가: 0
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DATA
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회반 지수 (CP-I)

56.7 / 100
전체 5,697개 중 758위 · 상위 14%

데이터 마이닝·데이터베이스 분야 336개 중 38위

학술적 인정 (35%)
58
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
76
커뮤니티 관심도 (10%)
29
공개 자료 충실도 (15%)
55

사용한 입력: 수록 등급: ICORE C · 확인되는 개최 횟수: 16 · 회반에서 팔로우 중인 연구자: 5명 · 지난 24개월 동안 이 페이지를 연 연구자: 4명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 최우수 논문 기록 (+2.3)
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신뢰도 80% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.1 · 산출일 2026-10-12

논문 모집

DATA 2027 (International Conference on Data Science, Technology and Applications) is a ICORE C conference held in Rome, Italy on 2027-07-19. The paper submission deadline is 2027-03-25. Acceptance notifications are sent on 2027-05-17.

SCOPE The purpose of the International Conference on Data Science, Technology and Applications (DATA) is to bring together researchers, engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data. Papers describing advanced methodologies, prototypes, systems, tools and techniques and general survey papers indicating future directions are also encouraged. Papers describing original work are invited in any of the areas listed. Accepted papers, presented at the conference by one of the authors, will be published in the conference proceedings. Acceptance will be based on quality, relevance and originality. Both full research papers and work-in-progress are welcome. There will be both oral and poster sessions. Special sessions, dedicated to case-studies and commercial presentations, as well as demos or tutorials dedicated to technical/scientific topics are also envisaged: companies interested in presenting their products/methodologies or researchers interested in holding a tutorial, workshop or special session are invited to contact the conference secretariat or visit the conference website. CONFERENCE AREAS Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas: 1. DATA SCIENCE & MACHINE LEARNING 2. DATABASES & DATA MANAGEMENT 3. DATA ENGINEERING, INFRASTRUCTURE AND BUSINESS APPLICATIONS 4. DATA ANALYTICS & VISUALIZATION 5. DATA PRIVACY & SECURITY, ETHICS & GOVERNANCE 6. DATA IN INDUSTRY AND EMERGING TRENDS IN DATA AREA 1: DATA SCIENCE & MACHINE LEARNING Advanced Machine Learning Algorithms Natural Language Processing Machine Learning for Large Datasets Computer Vision Explainable AI AutoML & Hyperparameter Tuning Time Series Analysis Predictive Modeling Pattern Recognition Data Mining Techniques AREA 2: DATABASES & DATA MANAGEMENT Relational vs. NoSQL Databases Database Scalability & Performance Tuning Distributed Databases & Sharding Database Security & Access Control SQL vs. NewSQL: Choosing the Right Database Graph Databases & Complex Network Analysis Database Migration & Integration Strategies AREA 3: DATA ENGINEERING, INFRASTRUCTURE AND BUSINESS APPLICATIONS Data Pipelines & ETL Real-Time Data Processing Cloud Data Infrastructure Big Data Technologies Data Governance & Quality Business Intelligence Open Data and Linked Data Data Fusion Social Web Search and Mining AREA 4: DATA ANALYTICS & VISUALIZATION Advanced Data Analytics Statistics and Exploratory Data Analysis Unstructured Data Analytics Data Storytelling Dashboards & BI Tools Geospatial Analytics Interactive Data Visualization AREA 5: DATA PRIVACY & SECURITY, ETHICS & GOVERNANCE Threat Detection & Prevention Data Governance Frameworks Bias in Data Data Ownership & Control Data Sovereignty AREA 6: DATA IN INDUSTRY AND EMERGING TRENDS IN DATA Data in Finance, Healthcare, Retail & E-commerce, Manufacturing, Marketing Data-Driven Innovation Scalability & Performance Collaborative Data Science Data for Crisis Management Quantum Computing & Data Edge Computing & Data Synthetic Data Digital Twins
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