Abbrevation
BigDataScience
City
Stanford
Country
United States
Deadline Paper
Start Date
End Date
Abstract

<p style="text&#8211;align: justify;"><b>Topics of particular interest include, but are not limited to:</b></p><strong>&#8211; Big Data Science</strong>: Theories, models, algorithms, benchmarking, curation, and methods for understanding big data<strong><br>&#8211; Big Data Computing</strong>: Infrastructures, tools, programming, architectures, benchmarking, and testing of big data systems using Map/Reduce, Hadoop and others<strong><br>&#8211; Big Data Mining</strong>: Acquisition, representation, indexing, storage, management, processing, pre&#8211;processing and post&#8211;processing of big data<strong><br>&#8211; Big Data Analytics</strong>: Metrics, frameworks, evaluation, tools, analysis, visualization of big data<strong><br>&#8211; Big Data Understanding</strong>: learning, knowledge discovery, business and consumer intelligence, user behavior, community discovery<strong><br>&#8211; Big Data Applications</strong>: Industrial and scientific applications of big data such as search, recommendations, business intelligence, marketing, social media, good practices and reproducibility&#046;<strong><br>&#8211; Big Data Privacy and Security</strong>: Data privacy enhancing technologies, privacy&#8211;preserving computing, risk analysis, modeling, and management, trustworthy computing, access control<br>