Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. Graph is a natural data structure used for modeling complex objects. Frequent subgraph mining is another active research topic in data mining . A graph is a general model to represent data and has been used in many domains like cheminformatics and bioinformatics. Mining patterns from graph data...

As technology advances, streams of data can be produced in many applications such as social networks, sensor networks, bioinformatics, and chemical informatics. These kinds of streaming data share a property in common—namely, they can be modeled in terms of graph-structured data. Here, the data streams generated by graph data sources in these applications are graph streams. To extract implicit,...

Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. Graph is a natural data structure used for modeling complex objects. Frequent subgraph mining is another active research topic in data mining . A graph is a general model to represent data and has been used in many domains like cheminformatics and bioinformatics. Mining patterns from graph data...

One of the main differences between ILP and graph mining is that while pattern matching in ILP is mainly defined by homomorphism (subsumption), it is the subgraph isomorphism in graph mining. Using that subgraph isomorphisms are injective homomorphisms, we bridge the gap between the two pattern matching operators with partially injective homomorphisms, which are homomorphisms requiring the inje...

Graphs are everywhere: social networks, the World Wide Web, biological networks, and many more. The sizes of graphs are growing at unprecedented rate, spanning millions and billions of nodes and edges. What are the patterns in large graphs, spanning Giga, Tera, and heading toward Peta bytes? What are the best tools, and how can they help us solve graph mining problems? How do we scale up algori...

Molecular dynamics simulation method is widely used to calculate and understand a wide range of properties of materials. A lot of research efforts have been focused on simulation techniques but relatively fewer works are done on methods for analyzing the simulation results. Large-scale simulations usually generate massive amounts of data, which make manual analysis infeasible, particularly when...