TL;DR
This paper proposes Scenemash, a system that generates multimodal summaries of multiple alternative routes between locations in a city by jointly analysing distributions of a large number of semantic concepts detected in the visual content and latent topics extracted from associated text.
An integrated framework combining Topic-RoBERTa, topic-level semantic network analysis, and Graph Attention Networks (GAT) to extract experience topics and model their semantic associations and offer valuable insights for tourism management and service optimization is presented.
This study introduces an approach leveraging deep neural networks to identify high-level, abstract concepts in visual user-generated content (UGC) for restaurants, and proposes two weak labeling methods: one utilizing existing restaurant-quality signals, and the other extracting relevant labels from review texts via qu...
The need for task-specific designs that support cross-city preference transfer, semantic grounding, and scalable reasoning over unseen destination inventories is highlighted, with results highlighting the need for task-specific designs that support cross-city preference transfer, semantic grounding, and scalable reason...
This survey presents fundamental concepts, methods, and challenges related to knowledge discovery from urban trajectory data, including data acquisition, preprocessing, mining, and practical applications, ensuring that each stage is optimized to contribute to the overall performance of the mobility knowledge discovery...
A case study is model by using the OSM history files, contributor profile pages, and the geographies of contributor interest to construct “the story of OpenStreetMap” in the small agricultural town of Othello, Washington, USA, and evaluating the map’s completeness by performing a walking survey of Othello’s commercial...
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