2021 Workshop on Big Data Sciences (WBDS 2021)

Conference / Summit (onsite)
Big Data & Analytics

Address: Venue to be announced, Paris, France
Date: 15 to 17 Oct '21

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Publication: 

Paper accepted by WBDS 2021 will be published in one of the following Journals after review process. 


▶Journal of Advances in Information Technology (JAIT, ISSN: 1798-2340 (Online)) 

Abstracting/Indexing: Scopus (Since 2020), EBSCO; Google Scholar; CrossRef; etc. 


▶International Journal of Computer Theory and Engineering (IJCTE, ISSN: 1793-8201 (Print)) 

Abstracting/Indexing: Index Copernicus, Electronic Journals Library, Google Scholar, Ulrich's Periodicals Directory, Crossref, ProQuest, WorldCat, EBSCO, and EI (INSPEC, IET), etc. 


Contact: 

☞ Conference secretary: Ms. Yolanda Dong 

☏ Tel: +86-18080013977 

✉ Email: wbds@iacsit.org  

✔ Website: http://www.wbds.org/ 

Workshop on Big Data Sciences (WBDS 2021) will be held in Paris, France during October 15-17, 2021.

Big data is a big deal for industries. The onslaught of IoT and other connected devices has created a massive uptick in the amount of information organizations collect, manage and analyze. Along with big data comes the potential to unlock big insights – for every industry, large to small.

WBDS allows academia to meet industry from the international community to exchange experiences, demonstrate their studies and further advance big data science. You will also have a chance to discover the fascinating culture and architecture of Paris, try out the local cuisine, and discover the city's hidden gems.

Topics of interest for submission include, but are not limited to: (CFP Flyer

Topic area 1: Big Data Science and Foundations

Novel Theoretical Models for Big Data
New Computational Models for Big Data
Data and Information Quality for Big Data
New Data Standards
Cloud/Grid/Stream Computing for Big Data
High Performance/Parallel Computing Platforms for Big Data
Energy-efficient Computing for Big Data
Software Techniques and Architectures in Cloud/Grid/Stream Computing
Big Data Open Platforms
New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
Software Systems to Support Big Data Computing

Topic area 2: Big Data Management

Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
Big Data Search Architectures, Scalability and Efficiency
Data Acquisition, Integration, Cleaning, and Best Practices
Visualization Analytics for Big Data
Computational Modeling and Data Integration
Large-scale Recommendation Systems and Social Media Systems
Cloud/Grid/Stream Data Mining- Big Velocity Data
Link and Graph Mining
Semantic-based Data Mining and Data Pre-processing
Mobility and Big Data
Multimedia and Multi-structured Data- Big Variety Data

Topic area 3: Big Data Search and Mining

Social Web Search and Mining
Web Search
Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
Big Data Search Architectures, Scalability and Efficiency
Data Acquisition, Integration, Cleaning, and Best Practices
Visualization Analytics for Big Data
Computational Modeling and Data Integration
Large-scale Recommendation Systems and Social Media Systems
Cloud/Grid/StreamData Mining- Big Velocity Data
Link and Graph Mining
Semantic-based Data Mining and Data Pre-processing
Mobility and Big Data
Multimedia and Multi-structured Data-Big Variety Data

Workshop on Big Data Sciences (WBDS 2021) will be held in Paris, France during October 15-17, 2021.

Big data is a big deal for industries. The onslaught of IoT and other connected devices has created a massive uptick in the amount of information organizations collect, manage and analyze. Along with big data comes the potential to unlock big insights – for every industry, large to small.

WBDS allows academia to meet industry from the international community to exchange experiences, demonstrate their studies and further advance big data science. You will also have a chance to discover the fascinating culture and architecture of Paris, try out the local cuisine, and discover the city's hidden gems.

Topics of interest for submission include, but are not limited to: (CFP Flyer

Topic area 1: Big Data Science and Foundations

Novel Theoretical Models for Big Data
New Computational Models for Big Data
Data and Information Quality for Big Data
New Data Standards
Cloud/Grid/Stream Computing for Big Data
High Performance/Parallel Computing Platforms for Big Data
Energy-efficient Computing for Big Data
Software Techniques and Architectures in Cloud/Grid/Stream Computing
Big Data Open Platforms
New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
Software Systems to Support Big Data Computing

Topic area 2: Big Data Management

Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
Big Data Search Architectures, Scalability and Efficiency
Data Acquisition, Integration, Cleaning, and Best Practices
Visualization Analytics for Big Data
Computational Modeling and Data Integration
Large-scale Recommendation Systems and Social Media Systems
Cloud/Grid/Stream Data Mining- Big Velocity Data
Link and Graph Mining
Semantic-based Data Mining and Data Pre-processing
Mobility and Big Data
Multimedia and Multi-structured Data- Big Variety Data

Topic area 3: Big Data Search and Mining

Social Web Search and Mining
Web Search
Algorithms and Systems for Big Data Search
Distributed, and Peer-to-peer Search
Big Data Search Architectures, Scalability and Efficiency
Data Acquisition, Integration, Cleaning, and Best Practices
Visualization Analytics for Big Data
Computational Modeling and Data Integration
Large-scale Recommendation Systems and Social Media Systems
Cloud/Grid/StreamData Mining- Big Velocity Data
Link and Graph Mining
Semantic-based Data Mining and Data Pre-processing
Mobility and Big Data
Multimedia and Multi-structured Data-Big Variety Data

Xiaojiang Du

IEEE Fellow

IConf

Media Partner

Venue

Venue to be announced

Organizer

International Association of Computer Science & Information Technology

Venue

Venue to be announced

Organizer

International Association of Computer Science & Information Technology

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