In the past decade, positioning system-enabled devices such as smartphones have become
most prevalent. This functionality brings the increasing popularity of location-based services …

An increasing number of related urban data sources have brought forth novel opportunities
for learning urban region representations, ie, embeddings. The embeddings describe latent …

Effective querying of data in the road networks is an important problem in the Internet of
vehicles. Aggregate nearest neighbor queries can return the objects that minimizes an …

As a major type of continuous spatial queries, the moving spatial keyword queries have
been studied extensively. Most existing studies focus on retrieving single objects, each of …

Large language models (LLMs) are advancing rapidly. Such models have demonstrated
strong capabilities in learning from large-scale (unstructured) text data and answering user …

The k nearest neighbor (kNN) query in road networks is a traditional query type in spatial
databases. This query has found new applications in the fast-growing location-based …

As a major type of continuous spatial queries, the moving nearest neighbor (NN) query has
been studied extensively. However, most existing studies have focused on only the query …

The moving kk nearest neighbor (M k NN) query has been studied extensively. Most of the
studies assume no obstacle in the space. However, obstacles like rivers, buildings and …

The moving k nearest neighbor query computes one's k nearest neighbor set and maintains
it while at move. This query is gaining importance due to the prevalent use of smart mobile …

Many modern applications in several domains such as sensor networks, financial
applications, web logs and click-streams operate on continuous, unbounded, rapid, time …