Existing graph mining algorithms typically assume that the dataset can fit into main memory. As many large graph datasets cannot satisfy this condition, truly scalable graph minin...
This paper proposes a two-step graph partitioning method to discover constrained clusters with an objective function that follows the well-known minmax clustering principle. Compar...
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...
We present a study of the web based user navigation patterns mining and propose a novel approach for clustering of user navigation patterns. The approach is based on the graph par...
Mehrdad Jalali, Norwati Mustapha, Ali Mamat, Nasir...
Existing graph mining algorithms typically assume that databases are relatively static and can fit into the main memory. Mining of subgraphs in a dynamic environment is currently ...