Statistical Network Analysis: Models, Issues, and New Directions: ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected PapersEdoardo M. Airoldi, David M. Blei, Stephen E. Fienberg Springer Science & Business Media, 20/07/2007 - 196 páginas This volume was prepared to share with a larger audience the exciting ideas and work presented at an ICML 2006 workshop of the same title. Network models have a long history. Sociologists and statisticians made major advances in the 1970s and 1980s, culminating in part with a number of substantial databases and the class of exponential random graph models and related methods in the early 1990s. Physicists and computer scientists came to this domain cons- erably later, but they enriched the array of models and approaches and began to tackle much larger networks and more complex forms of data. Our goal in organ- ing the workshop was to encourage a dialog among people coming from di?erent disciplinary perspectives and with di?erent methods, models, and tools. Both the workshop and the editing of the proceedings was a truly colla- rative e?ort on behalf of all six editors, but three in particular deserve special recognition. Anna Goldenberg and Alice Zheng were the driving force behind the entire enterprise and Edo Airoldi assisted on a number of the more important arrangements. |
Índice
Structural Inference of Hierarchies in Networks | 1 |
Emergent Features in Dynamic Structures | 14 |
Joint Group and Topic Discovery from Relations and Text | 28 |
A Brief Review of Some Recent Research | 45 |
Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis | 57 |
Exploratory Study of a New Model for Evolving Networks | 75 |
A Latent Space Model for Rank Data | 90 |
A Simple Model for Complex Networks with Arbitrary Degree Distribution and Clustering | 103 |
Discovering Functional Communities in Dynamical Networks | 140 |
Empirical Analysis of a Dynamic Social Network Built from PGP Keyrings | 158 |
A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring | 172 |
Age and Geographic Inferences of the LiveJournal Social Network | 176 |
Inferring Organizational Titles in Online Communication | 179 |
Learning Approximate MRFs from Large Transactional Data | 182 |
Panel Discussion | 186 |
Appendix | 195 |
Discrete Temporal Models of Social Networks | 115 |
Approximate Kalman Filters for Embedding AuthorWord Cooccurrence Data over Time | 126 |
Outras edições - Ver tudo
Palavras e frases frequentes
actors algorithm approximate average Bayesian behavior Berlin Heidelberg 2007 beta rhythm block models candidates Carnegie Mellon University clustering coefficient co-occurrence components compute configurations connected context coordinates corresponding dataset Debian degree distribution dendrogram denote dependence graph dyad dynamic E.M. Airoldi edges embedding entities ERGM estimates exponential family exponential random graph Fianna Fáil Figure functional communities Gaussian Gibbs sampling GT model Handcock Heiderian hierarchical ICML individuals inference interactions itemset iterations Journal Kalman filter key server key-ring labels latent space model Linux Machine Learning Markov chain matrix maximum likelihood MCMC method mixed membership network data network models neurons nodes observed pair parameters party posterior prediction probability random graph random graph models relations relationships represent sampling Science Senate Simmelian social network analysis statistical modeling stochastic block symmetric topics transition triads update values variables vector voter voting Wasserman weight