TY - JOUR AU - Chen, Lisi AU - Shang, Shuo PY - 2019/07/17 Y2 - 2024/03/28 TI - Region-Based Message Exploration over Spatio-Temporal Data Streams JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 33 IS - 01 SE - AAAI Technical Track: Applications DO - 10.1609/aaai.v33i01.3301873 UR - https://ojs.aaai.org/index.php/AAAI/article/view/3875 SP - 873-880 AB - <p>Massive amount of spatio-temporal data that contain location and text content are being generated by location-based social media. These spatio-temporal messages cover a wide range of topics. It is of great significance to discover local trending topics based on users’ location-based and topicbased requirements. We develop a region-based message exploration mechanism that retrieve spatio-temporal message clusters from a stream of spatio-temporal messages based on users’ preferences on message topic and message spatial distribution. Additionally, we propose a region summarization algorithm that finds a subset of representative messages in a cluster to summarize the topics and the spatial attributes of messages in the cluster. We evaluate the efficacy and efficiency of our proposal on two real-world datasets and the results demonstrate that our solution is capable of high efficiency and effectiveness compared with baselines.</p> ER -