We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
A large body of work has been devoted to identifying community structure in networks. A community is often though of as a set of nodes that has more connections between its member...
Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Mi...
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...
Recently, social text streams (e.g., blogs, web forums, and emails) have become ubiquitous with the evolution of the web. In some sense, social text streams are sensors of the rea...