A lot of research in graph mining has been devoted in the discovery of communities. Most of
the work has focused in the scenario where communities need to be discovered with only …

We witness an unprecedented proliferation of knowledge graphs that record millions of
entities and their relationships. While knowledge graphs are structure-flexible and content …

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 …

Given a large graph, how can we calculate the relevance between nodes fast and
accurately? Random walk with restart (RWR) provides a good measure for this purpose and …

Abstract Knowledge graphs (KGs) are a key ingredient for searching, browsing and
knowledge discovery activities. Motivated by the need to harness knowledge available in a …

Abstract The Semantic Web opens up new opportunities for the data mining research.
Semantic Web data is usually represented in the RDF triple format (subject, predicate …

When performing a software change task, programmers expend substantial effort
investigating a system's code base to find and understand just the code that is pertinent to a …

Searching for associations between entities is needed in many areas. On the Semantic Web,
it usually boils down to finding paths that connect two entities in an entity-relation graph …

Given a large graph, how can we calculate the relevance between nodes fast and
accurately? Random walk with restart (RWR) provides a good measure for this purpose and …

Searching for associations between entities is needed in many domains like national
security and bioinformatics. In recent years, it has been facilitated by the emergence of …