Mining frequent subgraphs is an important operation on graphs; it is defined as finding all
subgraphs that appear frequently in a database according to a given frequency threshold …

A knowledge graph contains many real-world facts that can be used to support various
analytical tasks, eg, exceptional fact discovery and the check of claims. In this work, we …

Methods and apparatus are provided for incremental frequent subgraph mining on dynamic
graphs. An exemplary subgraph mining method comprises maintaining a set of embeddings …

One of the key steps in data analysis is the exploration of data. For traditional relational data,
this process is facilitated by relational database management systems and the aggregates …

Using pattern mining techniques for building a predictive model is currently a popular topic
of research. The aim of these techniques is to obtain classifiers of better predictive …

Learning from graphs has become a popular research area due to the ubiquity of graph data
representing web pages, molecules, social networks, protein interaction networks etc …

A graph is a data structure that contains a set of nodes and a set of edges connecting these
nodes. Nodes represent objects while edges model relationships among these objects …

A simple and novel hyper linked data structure, H-struct, and a new frequent pattern mining
algorithm, H-mine, which takes advantage of H-struct data structure and dynamically adjusts …