Predicting the occurrence of links is a fundamental problem in networks. In the link
prediction problem we are given a snapshot of a network and would like to infer which …

Background High-throughput molecular interaction data have been used effectively to
prioritize candidate genes that are linked to a disease, based on the observation that the …

Social networks, sensor networks, biological networks, and many other information networks
can be modeled as a large graph. Graph vertices represent entities, and graph edges …

The field of market basket analysis, the search for meaningful associations in customer
purchase data, is one of the oldest areas of data mining. The typical solution involves the …

Knowledge bases of entities and relations (either constructed manually or automatically) are
behind many real world search engines, including those at Yahoo!, Microsoft, and Google …

Genome-wide linkage and association studies have demonstrated promise in identifying
genetic factors that influence health and disease. An important challenge is to narrow down …

This paper studies the problem of processing supergraph queries, that is, given a database
containing a set of graphs, find all the graphs in the database of which the query graph is a …

Increasingly complex databases need ever more sophisticated tools to help users
understand their schemas and interact with the data. Existing tools fall short of either …

Graph conductance queries, also known as personalized PageRank and related to random
walks with restarts, were originally proposed to assign a hyperlink-based prestige score to …

Large graphs are difficult to represent, visualize, and understand. In this paper, we
introduce" gate graph" a new approach to perform graph simplification. A gate graph …