Marko A. Rodriguez
My name is Dr. Marko A. Rodriguez. I’m a business-oriented researcher studying the theory and application of graph, stream, and database technologies to problems across various industries. The technologies I work on have been commercialized in my past company Aurelius and currently in my present company RReduX.
Handbook of Graph Drawing and Visualization
Handbook of Graph Drawing and Visualization Roberto Tamassia, Editor CRC Press June 24, 2013 Chapters # Title Authors Pages Draft Date Status P Title and preface Roberto Tamassia 10 PDF 6/24/13 camera ready C Contents Roberto Tamassia 4 PDF 6/24/13 camera ready 1 Planarity testing and embedding Patrignani 42 PDF 6/24/13 camera ready 2 Crossings and planarization Buchheim, Chimani, Gutwenger, Jueng
Supervised Random Walks: Predicting and Recommending Links in Social Networks
Supervised Random Walks: Predicting and Recommending Links in Social Networks Lars Backstrom Facebook [email protected] Jure Leskovec Stanford University [email protected] ABSTRACT Predicting the occurrence of links is a fundamental problem in net- works. In the link prediction problem we are given a snapshot of a network and would like to infer which interactions among existing members are lik
Minimum spanning tree - Wikipedia
A planar graph and its minimum spanning tree. Each edge is labeled with its weight, which here is roughly proportional to its length. A minimum spanning tree (MST) or minimum weight spanning tree is a subset of the edges of a connected, edge-weighted undirected graph that connects all the vertices together, without any cycles and with the minimum possible total edge weight.[1] That is, it is a spa
The Graph Traversal Programming Pattern
A graph is a structure composed of a set of vertices (i.e.~nodes, dots) connected to one another by a set of edges (i.e.~links, lines). The concept of a graph has been around since the late 19th century, however, only in recent decades has there been a strong resurgence in the development of both graph theories and applications. In applied computing, since the late 1960s, the interlinked table str
Gephi - The Open Graph Viz Platform
Support us! We are non-profit. Help us to innovate and empower the community by donating only 8€: Applications Exploratory Data Analysis: intuition-oriented analysis by networks manipulations in real time. Link Analysis: revealing the underlying structures of associations between objects. Social Network Analysis: easy creation of social data connectors to map community organizations and small-worl
Large graph mining: patterns, tools and case studies
Large graph mining: patterns, tools and case studies Tutorial proposal for CIKM 2008, Napa Valley, California Christos Faloutsos and Hanghang Tong, Carnegie Mellon University Abstract How do graphs look like? How do they evolve over time? How can we find patterns, anomalies and regularities in them? How to find influential nodes in the network? We will present both theoretical results and algorith
ICML 2009 tutorial: Modeling Social and Information Networks: Opportunities for ML
Who should attend: Since network data arises in so many different areas of data mining and machine learning, this tutorial should be of theoretical and practical interest to a large part of the machine learning community. The tutorial will not require prior knowledge beyond the basic concepts covered in introductory machine learning and algorithms classes. Presenter: Jure Leskovec is an assistant
Jon Kleinberg's Homepage
Tisch University Professor Department of Computer Science Department of Information Science Cornell University Ithaca, NY 14853 I am a professor at Cornell University. My research focuses on algorithms and networks, the roles they play in large-scale social and information systems, and their broader societal implications. My work has been supported by an NSF Career Award, an ONR Young Investigator
Jure Leskovec @ CMU
I got Ph.D. from Machine Learning Department, School of Computer Science at Carnegie Mellon University in September 2008 (See the video!). My advisor was Christos Faloutsos. I am now a post-doc at Cornell working with Jon Kleinberg. I will be joining the Computer Science Department at Stanford Univesity as an assistant professor in Fall 2009. I did my undergraduate in Computer Science at Universit
NIPS 2008 Proceedings
Advances in Neural Information Processing Systems 21 (NIPS 2008) The papers below appear in Advances in Neural Information Processing Systems 21 edited by D. Koller and D. Schuurmans and Y. Bengio and L. Bottou. They are proceedings from the conference, "Neural Information Processing Systems 2008." Structure Learning in Human Sequential Decision-Making Daniel Acuna, Paul R. Schrater The Gaussian P
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PEGASUS: Peta-Scale Graph Mining System
Hacking the Graph Tech Talk (9/11/2010) | Julie Tung, an engineer on our Platform team, talks about how you can build great social applications using Social Plugins and the Graph API. This tech... | By Engineering at Meta | Facebook
Google Groups
U Kang
Amazon.co.jp: Graph Mining: Laws, Tools, and Case Studies: Chakrabarti, Deepayan, Faloutsos, Christos: 本
handoff-clust1k12h2.eps
neo4j open source nosql graph database
The Structure of Information Networks (Jon Kleinberg)
Tools for large graph mining: structure and diffusion
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