In the last decade, there has been a significant surge of interest in machine learning,
primarily driven by advancements in deep learning (DL). DL has emerged as a powerful …

Background: In the context of Warehouse Management Systems, knowledge related to
motion trajectory prediction methods utilizing machine learning techniques seems to be …

Identifying opinion leaders in social networks, particularly in social media, is a crucial
marketing strategy. These individuals have a considerable influence on the purchasing …

Interesting sequential patterns in human movement trajectories can provide valuable
knowledge for urban management, planning, and location-based business. Existing …

Measuring trajectory similarity is a fundamental algorithm in trajectory data mining, playing a
key role in trajectory clustering, pattern mining, and classification, for instance. However …

The effective association of multimodal data is the basis of massive multi-source
heterogeneous data sharing in the era of big data. How to realize data autonomous …

Advancements in tracking technologies like GPS, RFID and mobile devices have made
trajectory data collection widespread. This surge in tracking device usage and location …

This paper provides a review and comparative analysis of trajectory outlier detection
methods. It presents the definition of outliers in trajectory data and the existing types to …

Sports tourism, characterized by the fusion of sports activities and travel experiences, has
gained significant popularity in recent years. Efficiently planning and personalizing sports …

This review examines the implementation of AI-powered data warehouse solutions to
optimize big data management and utilization, analyzing 25 peer-reviewed articles …