Finding Route Hotspots in Large Labeled Networks

In many advanced network analysis applications, like social networks, e-commerce, and security, hotspots are generally considered as a group of vertices that tightly connected owing to the similar characteristics, such common habits location proximity. this article, we investigate formation from an alternative perspective considers routes along paths auxiliary information, attempt find route in large labeled networks. A hotspot is cohesive subgraph covered by set routes, these correspond same sequential pattern consisting vertices' labels. To best our knowledge, problem Finding Route Hotspots Large Labeled Networks has not been tackled literature. However, it challenging counting number #P-hard. Inspired observation sizes decrease with increasing lengths patterns, prove several anti-monotonicity properties hotspots, then develop scalable algorithm called FastRH can use effectively prune patterns cannot form any hotspots. addition, avoid duplicate computation overhead, judiciously design effective index structure RH-Index for storing information collectively, which also enables incremental updating efficient query processing. Our experimental results on real-world datasets clearly demonstrate effectiveness scalability proposed methods.