The goal of graph clustering is to partition vertices in a large graph into different clusters
based on various criteria such as vertex connectivity or neighborhood similarity. Graph …

Social network systems, like last. fm, play a significant role in Web 2.0, containing large
amounts of multimedia-enriched data that are enhanced both by explicit user-provided …

A heterogeneous information network is an information network composed of multiple types
of objects. Clustering on such a network may lead to better understanding of both hidden …

In this paper we study approximate landmark-based methods for point-to-point distance
estimation in very large networks. These methods involve selecting a subset of nodes as …

Background We propose an efficient and biologically sensitive algorithm based on repeated
random walks (RRW) for discovering functional modules, eg, complexes and pathways …

This paper focuses on community mining including community discovery and change-point
detection on dynamic weighted directed graphs (DWDG). Real networks such as e-mail, co …

Many modern applications are faced with the task of knowledge discovery in entity-
relationship graphs, such as domain-specific knowledge bases or social networks. Mining …

Set expansion refers to expanding a partial set of “seed” objects into a more complete set.
One system that does set expansion is SEAL (Set Expander for Any Language), which …

An important and well-studied problem is the production of semantic lexicons from a large
corpus. In this paper, we present a system named ASIA (Automatic Set Instance Acquirer) …

World Wide Web content continuously grows in size and importance. Furthermore, users ask
Web search engines to satisfy increasingly disparate information needs. New techniques …