Recently, a number of researchers have investigated a class of graph partitioning algorithms
that reduce the size of the graph by collapsing vertices and edges, partition the smaller …

Recommender systems apply knowledge discovery techniques to the problem of making
personalized recommendations for information, products or services during a live interaction. …

… George Karypis is an assistant professor of computer science at the University of Minnesota.
… Karypis has a PhD in computer science from the University of Minnesota. He is a member of …

This paper presents the results of an experimental study of some common document clustering
techniques. In particular, we compare the two main approaches to document clustering, …

In this paper, we present and study a class of graph partitioning algorithms that reduces the
size of the graph by collapsing vertices and edges, we find ak-way partitioning of the smaller …

The explosive growth of the world-wide-web and the emergence of e-commerce has led to
the development of recommender systems---a personalized information filtering technology …

Recommender systems apply statistical and knowledge discovery techniques to the problem
of making product recommendations during a live customer interaction and they are …

• What is needed to begin the work.(Initialization)• Who does what.(Work distribution)• Access
to work part.(Data/IO access)• Whether they need info from each other to finish their own …

Systemic lupus erythematosus (SLE) is a complex, inflammatory autoimmune disease that
affects multiple organ systems. We used global gene expression profiling of peripheral blood …

We investigate the use of dimensionality reduction to improve performance for a new class
of data analysis software called "recommender systems". Recommender systems apply …