What is this part about? (2009)
Jure Leskovec, Christos Faloutsos, Matrix Tools, John Peter, Mary Nick
Tutorial outline � Part 1: Structure and models for networks � What are properties of large graphs? � How do we model them? � Part 2: Dynamics of networks � Diffusion and cascading behavior...
� Key Obstacles in Clustering Contingency Tables (2009)
Jure Leskovec, Christos Faloutsos, Ajit Singh
� Part 1: Structure and models for networks � What are properties of large graphs? � How do we model them? � � Part 2: Dynamics of networks � Diffusion and cascading behavior � How do...
� Social network analysis: sociologists and (2009)
Jure Leskovec, Christos Faloutsos, Bernardo Huberman, Jon Kleinberg, Andreas Krause, Mary Mcglohon, ...
About the tutorial Introduce properties, models and tools for � large real‐world networks � diff diffusion i processes in networks through real mining applications � Goal: find patterns,...
• Virus propagation and Diffusion (cascading (2009)
Jure Leskovec, Christos Faloutsos, Bernardo Huberman, Jon Kleinberg, Andreas Krause, Mary Mcglohon, ...
� Part 1: Structure and models for networks � What are properties of large graphs? � How do we model them? � � Part 2: Dynamics of networks � Diffusion and cascading behavior � How do...
Information Propagation and Network Evolution on the Web (2009)
Mary Mcglohon, Jure Leskovec, Christos Faloutsos, Natalie Glance, Matthew Hurst
Using data gathered from blogs, this work seeks to understand the structure and formation of social networks, and the patterns of information propagation through these networks. Blogs have become an...
Monitoring Network Evolution using MDL (2009)
Jure Ferlež, Christos Faloutsos, Jure Leskovec, Dunja Mladenić, Marko Grobelnik
Abstract — Given publication titles and authors, what can we say about the evolution of scientific topics and communities over time? Which communities shrunk, which emerged, and which split, over...
Jure Leskovec, Christos Faloutsos, Deepay Chakrabarti, Natalie Glance, Bernardo Huberman, Jon Kleinberg, ...
Tutorial outline � Part 1: Structure and models for networks � What are properties of large graphs? � How do we model them? � Part 2: Dynamics of networks �...
Diffusion and Cascading Behavior – Part 1: Basic mathematical models (2009)
Jure Leskovec, Christos Faloutsos, Ajit Singh, Jeanne Vanbriesen, Virus Propagation
� Part 1: Structure and models for networks � What are properties of large graphs? � How do we model them? � Part 2: Dynamics of networks �...
Jure Leskovec, Christos Faloutsos, Bernardo Huberman, Jon Kleinberg, Andreas Krause, Mary Mcglohon, ...
� Social network analysis: sociologists and computer scientists –influence goes both ways � Large‐scale network data in “traditional ” sociological domains �...
Planetary-Scale Views on a Large Instant-Messaging Network (2008)
We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We examine characteristics and...
Kronecker Graphs: an approach to modeling networks (2008)
Leskovec, Jure, Chakrabarti, Deepayan, Kleinberg, Jon, Faloutsos, Christos, Gharamani, Zoubin
How can we model networks with a mathematically tractable model that allows for rigorous analysis of network properties? Networks exhibit a long list of surprising properties: heavy tails for the...
(who-eats-whom) Web & citations Internet Sexual network Yeast protein (2008)
Jure Leskovec, Christos Faloutsos, Avrim Blum, Jon Kleinberg, John Lafferty
interactions
Leskovec, Jure, Lang, Kevin J., Dasgupta, Anirban, Mahoney, Michael W.
A large body of work has been devoted to defining and identifying clusters or communities in social and information networks. We explore from a novel perspective several questions related to...
fakulta Karlovy univerzity (2008)
Jure Leskovec, Purnamrita Sarkar, Carlos Guestrin
Sensor networks are ad-hoc wireless networks of small, low-cost sensors, which can measure characteristics of their environment. Autonomous low-cost sensors often have limited battery life, and are...
Jure Leskovec, Natalie Glance, Carlos Guestrin, Bernardo Huberman, Jon Kleinberg, Andreas Krause, ...
� Social network analysis: sociologists and computer scientists –influence goes both ways – Large‐scale network data in “traditional ” sociological domains •...
honors Discovery and Data Mining, KDD 2007. Publications (2008)
Jure Leskovec, Advised Christos Faloutsos
Research Applied machine learning and large-scale data mining, focusing on the analysis and interests modeling of large real-world networks.
Jure Leskovec, B (c, Blog Networks, Power Grid
� Autonomous systems Florence families Karate club network Friendship network Collaboration network Networks of the real-world (2) � Biological networks � metabolic networks � food web �...
Learning Semantic Graph Mapping for Document Summarization (2008)
Jure Leskovec, Marko Grobelnik, Natasa Milic-frayling
Abstract. We present a method for summarizing document by creating a semantic graph of the original document and identifying the substructure of such a graph that can be used to extract sentences for...
GMine: A System for Scalable, Interactive Graph Visualization and Mining (2008)
José F. Rodrigues, Hanghang Tong, Christos Faloutsos, Jure Leskovec
Several graph visualization tools exist. However, they are not able to handle large graphs, and/or they do not allow interaction. We are interested on large graphs, with hundreds of thousands of...
Planetary-Scale Views on an Instant-Messaging Network (2008)
We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We examine characteristics and...
Epidemic Thresholds in Real Networks (2008)
Deepayan Chakrabarti, Yang Wang, Chenxi Wang, Jure Leskovec, Christos Faloutsos
How will a virus propagate in a real network? How long does it take to disinfect a network given particular values of infection rate and virus death rate? What is the single best node to immunize?...
Abstract Finding patterns in blog shapes and blog evolution (2008)
Mary Mcglohon, Jure Leskovec, Christos Faloutsos, Matthew Hurst, Natalie Glance
Can we cluster blogs into types by considering their typical posting and linking behavior? How do blogs evolve over time? In this work we answer these questions, by providing several sets of blog and...
honors Discovery and Data Mining, KDD 2007. Publications (2008)
Jure Leskovec, Advised Christos Faloutsos
Research Applied machine learning and large-scale data mining, focusing on the analysis and interests modeling of large real-world networks.
ABSTRACT The Dynamics of Viral Marketing ∗ (2008)
We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of...
Sampling from Large Graphs (2008)
Jure Leskovec Carnegie, Jure Leskovec
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.), but several of...
Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations (2008)
Jure Leskovec, Jon Kleinberg, Christos Faloutsos
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs,...
Monitoring Network Evolution using MDL. (2008)
Ferlez, Jure, Faloutsos, Christos, Leskovec, Jure, Mladenić, Dunja, Grobelnik, Marko
Given publication titles and authors, what can we say about the evolution of scientific topics and communities over time? Which communities shrunk, which emerged, and which split, over time? And,...
Microscopic Evolution of Social Networks (2008)
Leskovec, Jure, Backstrom, Lars, Kumar, Ravi, Tomkins, Andrew
We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale,...
Planetary-Scale Views on a Large Instant-Messaging Network (2008)
We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We ex- amine characteristics and...
Microscopic Evolution of Social Networks (2008)
Leskovec, Jure, Backstrom, Lars, Kumar, Ravi, Tomkins, Andrew
We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale,...
Statistical Properties of Community Structure in Large Social and Information Networks (2008)
Leskovec, Jure, Lang, Kevin, Dasgupta, Anirban, Mahoney, Michael
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 members than to the...
Planetary-Scale Views on a Large Instant-Messaging Network (2008)
We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We ex- amine characteristics and...
Mobile Call Graphs: Beyond Power-Law and Lognormal Distributions (2008)
Mukund, Seshadri, Machiraju, Sridhar, Sridharan, Ashwin, Bolot, Jean, Faloutsos, Christos, Leskovec, Jure
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distributions of the...
Statistical properties of community structure in large social and information networks (2008)
Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Michael W. Mahoney
A large body of work has been devoted to defining and identifying communities in social and information networks, i.e., in graphs in which the nodes represent underlying social entities and the edges...
Cascading Behavior in Large Blog Graphs (2007)
Leskovec, Jure, McGlohon, Mary, Faloutsos, Christos, Glance, Natalie, Hurst, Matthew
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work....
Cascading behavior in large blog graphs (2007)
Jure Leskovec, Mary Mcglohon, Christos Faloutsos, Natalie Glance, Matthew Hurst
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work....
Planetary-Scale Views on an Instant-Messaging Network ∗ (2007)
We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We examine characteristics and...
Information survival threshold in sensor and P2P networks (2007)
Deepayan Chakrabarti, Jure Leskovec, Christos Faloutsos, Samuel Madden, Carlos Guestrin, Michalis Faloutsos
Abstract—Consider a network of, say, sensors, or P2P nodes, or bluetooth-enabled cell-phones, where nodes transmit information to each other and where links and nodes can go up or down. Consider...
Information survival threshold in sensor and P2P networks (2007)
Deepayan Chakrabarti, Jure Leskovec, Christos Faloutsos, Samuel Madden, Carlos Guestrin, Michalis Faloutsos
Abstract—Consider a network of, say, sensors, or P2P nodes, or bluetooth-enabled cell-phones, where nodes transmit information to each other and where links and nodes can go up or down. Consider...
Cascading behavior in large blog graphs (2007)
Jure Leskovec, Mary Mcglohon, Christos Faloutsos, Natalie Glance, Matthew Hurst
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work....
Web projections: Learning from contextual subgraphs of the web (2007)
Graphical relationships among web pages have been leveraged as sources of information in methods for ranking search results. To date, specific graphical properties have been used in these analyses....
Information survival threshold in sensor and P2P networks (2007)
Deepayan Chakrabarti, Jure Leskovec, Christos Faloutsos, Samuel Madden, Carlos Guestrin, Michalis Faloutsos
Abstract — Consider a network of, say, sensors, or P2P nodes, or bluetooth-enabled cell-phones, where nodes transmit information to each other and where links and nodes can go up or down. Consider...
Information survival threshold in sensor and P2P networks (2007)
Deepayan Chakrabarti, Jure Leskovec, Christos Faloutsos, Samuel Madden, Carlos Guestrin, Michalis Faloutsos
Abstract — Consider a network of, say, sensors, or P2P nodes, or bluetooth-enabled cell-phones, where nodes transmit information to each other and where links and nodes can go up or down. Consider...
Web projections: Learning from contextual subgraphs of the web (2007)
Graphical relationships among web pages have been leveraged as sources of information in methods for ranking search results. To date, specific graphical properties have been used in these analyses....
Finding Patterns in Blog Shapes and Blog Evolution (2007)
Mary Mcglohon, Jure Leskovec, Christos Faloutsos, Matthew Hurst, Natalie Glance, Mary Mcglohon, ...
Can we cluster blogs into types by considering their typical posting and linking behavior? How do blogs evolve over time? In this work we answer these questions, by providing several sets of blog and...
Cost-effective Outbreak Detection in Networks (2007)
Leskovec, Jure, Krause, Andreas, Guestrin, Carlos, Faloutsos, Christos, VanBriesen, Jeanne, Glance, Natalie
Given a water distribution network, where should we place sensors to quickly detect contaminants? Or, which blogs should we read to avoid missing important stories? These seemingly different problems...
The Dynamics of Viral Marketing (2007)
Leskovec, Jure, Adamic, Lada, Huberman, Bernardo
We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of...
Cascading behavior in large blog graphs (2007)
Jure Leskovec, Mary Mcglohon, Christos Faloutsos, Natalie Glance, Matthew Hurst
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work....
Graph Evolution: Densification and Shrinking Diameters (2006)
Leskovec, Jure, Kleinberg, Jon, Faloutsos, Christos
How do real graphs evolve over time? What are ``normal'' growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying...
Laws of Graph Evolution: Densification and Shrinking Diameters (2006)
Jure Leskovec, Jon Kleinberg, Christos Faloutsos
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs,...
Data Association for Topic Intensity Tracking (2006)
Andreas Krause, Jure Leskovec, Carlos Guestrin
We present a unified model of what was traditionally viewed as two separate tasks: data association and intensity tracking of multiple topics over time. In the data association part, the task is to...
Cascading behavior in large blog graphs: Patterns and a model (2006)
Jure Leskovec, Mary Mcglohon, Christos Faloutsos, Natalie Glance, Matthew Hurst
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work....
Worldwide buzz: Planetary-scale views on an instant-messaging network (2006)
We present a study of anonymized data capturing high-level communication activities within the Microsoft Instant Messenger network. We analyze properties of the communication network defined by user...
Cascading behavior in large blog graphs: Patterns and a model (2006)
Jure Leskovec, Jure Leskovec, Mary Mcglohon, Mary Mcglohon, Christos Faloutsos, Christos Faloutsos, ...
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work....
Cascading behavior in large blog graphs: Patterns and a model (2006)
Jure Leskovec, Mary Mcglohon, Christos Faloutsos, Natalie Glance, Matthew Hurst
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work....
Modeling link qualities in a sensor network (2005)
Leskovec, Jure, Sarkar, Purnamrita, Guestrin, Carlos
Sensor networks are ad-hoc wireless networks of small, low-cost sensors, which can measure characteristics of their environment. Autonomous low-cost sensors often have limited battery life, and are...
Leskovec, Jure, Chakrabarti, Deepay, Kleinberg, Jon, Faloutsos, Christos
How can we generate realistic graphs? In addition, how can we do so with a mathematically tractable model that makes it feasible to analyze their properties rigorously? Real graphs obey a long list...
The Dynamics of Viral Marketing (2005)
Leskovec, Jure, Adamic, Lada A., Huberman, Bernardo A.
We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of...
Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations (2005)
Leskovec, Jure, Kleinberg, Jon, Faloutsos, Christos
How do real graphs evolve over time? What are ``normal'' growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying...
Leskovec, Jure, Milic-Frayling, Natasa, Grobelnik, Marko
Automatic document summarization is a problem of creating a document surrogate that adequately represents the full document content. We aim at a summarization system that can replicate the quality of...
Semantic Text Features from Small World Graphs (2005)
Leskovec, Jure, Shawe-Taylor, John
We present a set of methods for creating a semantic representation from a collection of textual documents. Given a document collection we use a simple algorithm to connect the documents into a tree...
Jure Leskovec, Natasa Milic-frayling, Marko Grobelnik
Automatic document summarization is a problem of creating a document surrogate that adequately represents the full document content. We aim at a summarization system that can replicate the quality of...
The Dynamics of Viral Marketing (2005)
Jure Leskovec, Lada Adamic, Bernardo Huberman
We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observed the propagation of...
Patterns of Influence in a Recommendation Network (2005)
Jure Leskovec, Ajit Singh, Jon Kleinberg
Information cascades are phenomena in which individuals adopt a new action or idea due to influence by others. As such a process spreads through an underlying social network, it can result in...
Learning Sub-structures of Document Semantic Graphs for Document Summarization (2004)
Leskovec, Jure, Grobelnik, Marko, Milic-Frayling, Natasa
In this paper we present a method for summarizing document by creating a semantic graph of the original document and identifying the substructure of such a graph that can be used to extract sentences...
Linear Programming Boosting for Uneven Datasets (2004)
Leskovec, Jure, Shawe-Taylor, John
The paper extends the notion of linear programming boosting to handle uneven datasets. Extensive experiments with text classification problem compare the performance of a number of different boosting...
The Download Estimation task on KDD Cup 2003 (2003)
This paper describes our work on the Download Estimation task for KDD Cup 2003. The task requires us to estimate how many times a paper has been downloaded in the first 60 days after it has been...
The Download Estimation Task on KDD Cup 2003 (2003)
Janez Brank And, Janez Brank, Jure Leskovec
This paper describes our work on the Download Estimation task for KDD Cup 2003. The task requires us to estimate how many times a paper has been downloaded in the first 60 days after it has been...