Contextual Behabiour Predictions in Dynamic Mobile E-commerce

动态移动电子商务中的情境行为预测

• 批准号: DP220103717
• 负责人: Prof Guandong Xu
• 金额: $ 29.13万
• 依托单位: University of Technology Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2022
• 资助国家: 澳大利亚
• 起止时间: 2022-03-18 至 2025-03-17
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP220103717
• 关键词: Contextual; Behabiour; Predictions; Dynamic; Mobile

The project aims to address behaviour prediction and develop novel techniques and tools for modelling, predicting human behaviours and making effective recommendations based on ubiquitous user behaviour data in mobile e-commerce. The techniques enable multi-source data fusion, context learning and model adaptation, and dynamic recommendation with interpretability ability. Expected outcomes include advances in data analytics theory and informed decision-making. This provides significant benefits of not only placing Australia in the forefront of exploiting multimodal user behaviour big data in dynamic e-commerce but also transforming Australian government and businesses to intelligent and contextual services adaptive to complex situations.

该项目旨在解决行为预测问题，开发新颖的技术和工具，用于建模、预测人类行为并根据移动电子商务中无处不在的用户行为数据提出有效的推荐。这些技术能够实现多源数据融合、上下文学习和模型自适应以及具有可解释性的动态推荐。预期成果包括数据分析理论和明智决策的进步。这带来了巨大的好处，不仅使澳大利亚处于利用动态电子商务中多模式用户行为大数据的前沿，而且使澳大利亚政府和企业转变为适应复杂情况的智能和情境服务。