IEEE Big Data 2021

Big Data technology has been one of key engines driving the new industrial revolution. However, the majority of current Big Data research efforts have been devoted to single-modal data analysis, which leads to a huge gap in performance when algorithms are carried out separately. Although significant progress has been made, single-modal data is often insufficient to derive accurate and robust models in many applications. Multimodal is the most general form for information representation and delivery in a real world. Multimodal data analytics algorithms often outperform single modal data analytics in many real-world problems. This workshop aims to generate momentum around this topic of growing interest, and to encourage interdisciplinary interaction and collaboration between Natural Language Processing (NLP), computer vision, machine learning, multimedia, robotics, Human-Computer Interaction (HCI), cloud computing, Internet of Things (IoT), and geospatial communities. It serves as a forum to bring together active researchers and practitioners from academia and industry to share their recent advances in this promising area.