Anomaly analysis is of great interest to diverse fields, including data mining and machine
learning, and plays a critical role in a wide range of applications, such as medical health …

Clustering is an unsupervised process which aims to discover regularities and underlying
structures in data. Constrained clustering extends clustering in such a way that expert …

Artificial intelligence (AI) based business process optimization has a significant impact on a
country's economic development. We argue that the use of artificial neural networks in …

Outlier identification is an important technology to improve the credibility of data and aims at
detecting patterns that rarely appear and exhibit a significant difference from other data …

Predicting travel trajectory of vehicles can not only provide personalized services to users,
but also have a certain effect on traffic guidance and traffic control. In this paper, we build a …

Geo-located social media provide a wealth of information that describes urban areas based
on user descriptions and comments. Such data makes possible to identify meaningful city …

Geo-located social media provide a large amount of information describing urban areas
based on user descriptions and comments. Such data make possible to identify meaningful …

Outlier detection consists in detecting anomalous observations from data. During the past
decade, outlier detection methods were proposed using the concept of frequent patterns …

Pattern mining in numerical data remains a challenging task due to the pattern search space
that becomes potentially infinite with real-valued dimensions. Most approaches reluctantly …

Dynamic networks are ubiquitous in many domains for modelling evolving graph-structured
data and detecting changes allows us to understand the dynamic of the domain …