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...
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
In this paper, we present a framework for mining diverging patterns, a new type of contrast patterns whose frequency changes significantly differently in two data sets, e.g., it c...
Relational graphs are widely used in modeling large scale networks such as biological networks and social networks. In this kind of graph, connectivity becomes critical in identif...