Conference Information
BigDataSE 2022: International Conference on Big Data Science and Engineering
http://www.ieee-hust-ncc.org/2022/BigDataSE/Submission Date: |
2022-07-15 Extended |
Notification Date: |
2022-08-15 |
Conference Date: |
2022-10-28 |
Location: |
Wuhan, China |
Years: |
16 |
Viewed: 17349 Tracked: 16 Attend: 0
Call For Papers
Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud computing platforms, and MapReduce. BigDataSE 2022 topics include, but are not limited to the following: Trust semantics, metrics and models Systems, Models and Algorithms Big Data novel theory, algorithm and applications Big Data standards Big Data mining and analytics Big Data Infrastructure, MapReduce and Cloud Computing Big Data visualization Big Data curation and management Big Data semantics, scientific discovery and intelligence Big Data performance analysis and large-scale deployment Security, privacy, trust, and legal issues to big data Big Data vs Big Business and Big Industry Large data stream processing on cloud Large incremental datasets on cloud Distributed and federated datasets NoSQL data stores and DB scalability Big Data placement, scheduling, and optimization Distributed file systems for Big Data MapReduce for Big Data processing, resource scheduling and SLA Performance characterization, evaluation and optimization Simulation and debugging systems and tools for MapReduce and Big Data Volume, Velocity, Variety, Value and Veracity of Big Data Multiple source data processing and integration with MapReduce Storage and computation management of Big Data Large-scale big data workflow management Mobility and big data Sensor network, social network and big data Big data applications
Last updated by Yuan Tian in 2022-07-08
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