The adaptive processing of graph data is a long-standing research topic that has been lately
consolidated as a theme of major interest in the deep learning community. The snap …

Feature selection, as a data preprocessing strategy, has been proven to be effective and
efficient in preparing data (especially high-dimensional data) for various data-mining and …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Releasing social network data could seriously breach user privacy. User profile and
friendship relations are inherently private. Unfortunately, sensitive information may be …

We present DeepWalk, a novel approach for learning latent representations of vertices in a
network. These latent representations encode social relations in a continuous vector space …

Nowadays, the growth of the high-throughput technologies has resulted in exponential
growth in the harvested data with respect to both dimensionality and sample size. The trend …

The problem of classification has been widely studied in the data mining, machine learning,
database, and information retrieval communities with applications in a number of diverse …

Credit scoring is without a doubt one of the oldest applications of analytics. In recent years, a
multitude of sophisticated classification techniques have been developed to improve the …

Most objects and data in the real world are of multiple types, interconnected, forming
complex, heterogeneous but often semi-structured information networks. However, most …