Rok Sosic
Jure Leskovec
ABSTRACT
Many techniques for the modeling, analysis and optimization of Web related datasets are based on studies of large scale networks, where a network can contain hundreds of millions of nodes and billions of edges. Network analysis tools must provide not only extensive functionality, but also high performance in processing these large networks. The tutorial will present Stanford Network Analysis Platform (SNAP), a general purpose, high performance system for analysis and manipulation of large networks. SNAP is being used widely in studies of the Web datasets. SNAP consists of open source software, which provides a rich set of functions for performing network analytics, and a popular repository of publicly available real world network datasets. SNAP software APIs are available in Python and C++.
The tutorial will cover all aspects of SNAP, including APIs and datasets. The tutorial will include a hands-on component, where the participants will have the opportunity to use SNAP on their computers.
- Jure Leskovec and Andrej Krevl. SNAP Datasets: Stanford large network dataset collection. http://snap.stanford.edu/data, June 201Google Scholar
- Jure Leskovec and Rok Sosic. SNAP: A general purpose network analysis and graph mining library in C++. http://snap.stanford.edu/snap, June 2014.Google Scholar
Index Terms
- Large Scale Network Analytics with SNAP: Tutorial at the World Wide Web 2015 Conference
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