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.

MMBD 2022 Accepted Papers & Program Schedule

Dec. 17, 2022, Japan Standard Time (JST) or Dec. 16, 2022, U.S. Eastern Time (EST)


Please login in the IEEE Big Data - MMBD 2022 Virtual Conference Platform with your registered email address.
Time (JST) Dec. 17 Time (EST) Dec. 16 Type Paper Title Author(s) Session Chair
8:00-8:15 18:00-18:15 Short On the Use of Convolutional Neural Networks for Palm Vein Recognition Mohamed Eladlani, Larbi Boubchir, Said Si Kaddour, and Boubaker Daachi Dr. Lindi Liao
8:15-8:40 18:15-18:40 Full Radiopaths: Deep Multimodal Analysis on Chest Radiographs Mohammad Kohankhaki, Ahmad Ayad, Mahdi Barhoush, and Anke Schmeink
8:40-9:20 18:40-19:20   Keynote:
Social Event Mining and Impact Forecasting with Heterogeneous Spatiotemporal Data
Dr. Kaiqun Fu
9:20-9:25 19:20-19:25   Cyber Coffee Break  
9:25-9:50 19:25-19:50 Full Twitter Bot Identification: An Anomaly Detection Approach Lulwah Alkulaib, Yanshen Sun, Lei Zhang, and Chang-Tien Lu Dr. Kaiqun Fu
9:50-10:15 19:50-20:15 Full Multimodal Lyrics-Rhythm Matching Callie Liao, Duoduo Liao, and Jesse Guessford
10:15-10:40 20:15-20:40 Full Simulating Fake News Dissemination on Twitter with Multivariate Hawkes Processes Yichen Jiang and Michael Porter
10:40-11:05 20:40-21:05 Full EBEM: An Enhanced Bi-encoder Model for Word Sense Disambiguation Xianglong Xiao, Hongguang Xu, and Ke Xu
11:05-11:10 21:05-21:10   Cyber Coffee Break  
11:10-11:25 21:10-21:25 Short Multimodal Deep Homography Estimation Using a Domain Adaptation Generative Adversarial Network Thomas Pouplin, Hughes Perreault, Benoit Debaque, Marc-Antoine Drouin, Nicolas Duclos-Hindie, and Simon Roy Dr. Lindi Liao
11:25-11:40 21:25-21:40 Short Truth or Fiction: Multimodal Learning Applied to Earnings Calls Jamshed Kaikaus, Jessen Hobson, and Robert Brunner
11:40-11:55 21:40-21:55 Poster Attention-aware multi-modal RNN for deception detection Shun-Wen Hsiao and Cheng-Yuan Sun
11:55-12:10 21:55-22:10 Poster SQ2SV: Sequential Queries to Sequential Videos retrieval Injin Paek, Nayoung Choi, Seongjin Ha, Yuheun Kim, and Min Song
12:10-12:15 22:10-22:15   Closing Remarks  

*The program schedule is subject to change.