Data plays a critical role in human life. In the digital era, where data can be collected almost anywhere and anytime, people have access to a vast volume of real-time data that reflects their living environment differently. People can extract necessary information from these data to gain knowledge and become wiser. Nevertheless, data often comes from multiple sources and only reflects a small part of the big puzzle of life. Despite potentially missing some pieces, the goal is to capture the puzzle's image with the available pieces. The more pieces of data we can collect and assemble within a given frame, the faster we can solve the puzzle. The challenge becomes even more significant when dealing with multimodal data, cross-domain and cross-platform problems. A multimodal data puzzle would be one where pieces have different shapes and sizes. A cross-domain puzzle would be one where the pieces come from distinct sub-pictures. Finally, a cross-platform puzzle would be one where the pieces assembled come from different puzzles. But in all these scenarios, you still have to put the pieces together to get the entire picture. The proposed research topic of "Intelligent Cross-Data Analysis and Retrieval" aims to advance the field of cross-data analytics and retrieval and contribute to developing a more intelligent and sustainable society. This workshop welcomes researchers coming from diverse domains and disciplines, such as well-being, disaster prevention and mitigation, mobility, climate change, tourism, healthcare, and more The proposed research topic of "Intelligent Cross-Data Analysis and Retrieval" aims to advance the field of cross-data analytics and retrieval and contribute to developing a more intelligent and sustainable society. This workshop welcomes researchers from diverse domains and disciplines, including well-being, disaster prevention and mitigation, mobility, climate change, tourism, healthcare, and more.

Example topics of interest include but is not limited to the following:

Event-based cross-data retrieval Data mining and AI technology.

Multimodal complex event processing.

Transfer Learning and Transformers.

Multimodal self-supervised learning

Heterogeneous data association discovery.

Cross-datasets for Repeatable Experimentation.

Federated Analytics and Federated Learning for cross-data.

Privacy-public data collaboration.

Diverse multimodal data Integration.

Realization of a prosperous and independent region in which people and nature coexist

Intelligent cross-data analysis applications from different domains

Followed by the success of the ICMR-ICDAR 2020, ICMR-ICDAR 2021, and ICMR-ICDAR 2022 workshops on intelligent cross-data analytics and retrieval, this proposal aims to organize the third workshop that provides the playground to people interested in the workshop's topics. In this playground, people share their experiences and brave new ideas towards making cross-data more intelligent by compensating each type of data's strengths and propose a new way to analyze and retrieve cross-data under different perspectives.

The accepted papers are expected to be published in the workshop proceedings.