The requirement for appropriate ways to measure the similarity between data objects is a
common but vital task in various domains, such as data mining, machine learning and so on …

With precipitously growing demand to detect outliers in data streams, many studies have
been conducted aiming to develop extensions of well-known outlier detection algorithm …

In a variety of research areas, the weighted bag of vectors and the histogram are widely
used descriptors for complex objects. Both can be expressed as discrete distributions. D2 …

Quantitative data cleaning relies on the use of statistical methods to identify and repair data
quality problems while logical data cleaning tackles the same problems using various forms …

In the tourism industry, the implementation of effective strategies to promote destinations is
considered of utmost importance. Taking advantage of social media, Destination …

Data generated on location-aware social media provide rich information about the places
(shop** malls, restaurants, cafés, etc) where citizens spend their time. That information …

Trajectory-based spatiotemporal entity linking is to match the same moving object in different
datasets based on their movement traces. It is a fundamental step to support spatiotemporal …

The amount of spatial data in open data portals has increased rapidly, raising the demand
for spatial dataset search in large data repositories. In this paper, we tackle spatial dataset …

The prevalent adoption of GPS-enabled devices has witnessed an explosion of various
location-based services which produce a huge amount of trajectories monitoring an …

The Kuhn-Munkres (KM) algorithm is a classical combinatorial optimization algorithm that is
widely used for minimum cost bipartite matching in many real-world applications, such as …