Mining frequent subtrees from databases of labeled trees is a new research field that has
many practical applications in areas such as computer networks, Web mining …

The analysis of molecular networks, such as transcriptional, metabolic and protein
interaction networks, has progressed substantially because of the power of models from …

This newly expanded and updated second edition of the best-selling classic continues to
take the" mystery" out of designing algorithms, and analyzing their efficacy and efficiency …

Graph mining is an important research area within the domain of data mining. The field of
study concentrates on the identification of frequent subgraphs within graph data sets. The …

A key issue in software evolution analysis is the identification of particular changes that
occur across several versions of a program. We present change distilling, a tree differencing …

The application of semidefinite programming to the optimal power flow (OPF) problem has
recently attracted significant research interest. This paper provides advances in modeling …

While message-passing graph neural networks have clear limitations in approximating
permutation-equivariant functions over graphs or general relational data, more expressive …

MIMO-OFDM for LTE, WIFI and WIMAX: Coherent versus Non-Coherent and Cooperative
Turbo-Transceivers provides an up-to-date portrayal of wireless transmission based on …

Feature modeling is a notation and an approach for modeling commonality and variability in
product families. In their basic form, feature models contain mandatory/optional features …

A graph parameter is a numerical value assigned to a graph that describes specific
structural properties, such as size or connectivity. A” graph width parameter” measures the …