http://www.knowledgefrominformation.com Research trends on extracting knowledge from large repositories of information. Tue, 24 Jan 2012 20:51:25 +0000 http://backend.userland.com/rss092 en Even long journeys eventually come to an end. After 4 years of intensive research I successfully defended my doctoral dissertation at the University of Maryland. The thesis ties together my work on indexing and querying huge social networks and machine learning on multi-relational data under the common theme of social ... http://www.knowledgefrominformation.com/2011/12/20/phd-social-network-data-management/ Conference Paper, International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011, Kaohsiung, Taiwan Authors: Matthias Broecheler, Andrea Pugliese, VS Subrahmanian Direct link to paper Abstract Users querying massive social networks or RDF databases are often not 100% certain about what they are looking for due to the complexity of the query ... http://www.knowledgefrominformation.com/2011/07/28/probabilistic-subgraph-matching-on-huge-social-networks/ Workshop Paper, ICDE Workshop on Graph Data Management, 2011, Hannover, Germany Authors: Matthias Broecheler, Andrea Pugliese, VS Subrahmanian Direct link to paper Abstract As social network and RDF data grow dramatically in size to billions of edges, the ability to scalably answer queries posed over graph datasets becomes increasingly important. In this paper, we ... http://www.knowledgefrominformation.com/2011/04/16/budget-match-cost-effective-subgraph-matching-on-large-networks/ Abstract There is a growing interest in methods for exploiting causal or correlational dependencies in structured domains. Exploiting such dependencies often results in improved predictive performance on complex inference tasks in diverse domains such as information integration, natural language processing, and computer vision. In this presentation, we introduce probabilistic soft ... http://www.knowledgefrominformation.com/2010/12/03/probabilistic-soft-logic/ Workshop Paper, NIPS Workshop on Predictive Models in Personalized Medicine, 2010, Whistler, Canada Authors: Stephen H. Bach, Matthias Broecheler, Stanley Kok, and Lise Getoor Direct link to paper Abstract We introduce the concept of a decision-driven model, a probabilistic model that reasons directly over the uncertain information of interest to a decision maker. ... http://www.knowledgefrominformation.com/2010/11/15/decision-driven-models-with-probabilistic-soft-logic/ Conference Paper, Advances in Neural Information Processing Systems (NIPS), 2010, Vancouver, Canada Authors: Matthias Broecheler and Lise Getoor Direct link to paper Data set used in the experiments Abstract Continuous Markov random fields are a general formalism to model joint probability distributions over events with continuous outcomes. We prove that marginal computation for constrained ... http://www.knowledgefrominformation.com/2010/10/30/computing-marginal-distributions-over-continuous-markov-networks-for-statistical-relational-learning/ Conference Paper, Proceedings of the 2010 IEEE International Conference on Social Computing, Symposium Section Authors: Matthias Broecheler, Paulo Shakarian, and V.S. Subrahmanian Direct link to paper Abstract Multiple phenomena often diffuse through a social network, sometimes in competition with one another. Product adoption and political elections are two examples where network diffusion is inherently ... http://www.knowledgefrominformation.com/2010/08/01/a-scalable-framework-for-modeling-competitive-diffusion-in-social-networks/ Conference Paper, Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining, Odense, Denmark Authors: Matthias Bröcheler, Andrea Pugliese and V.S. Subrahmanian Direct link to paper 3rd Best Paper Award Abstract Subgraph matching is a key operation on graph data. Social network (SN) providers may want to find all subgraphs within ... http://www.knowledgefrominformation.com/2010/08/01/cosi-cloud-oriented-subgraph-identification-in-massive-social-networks/ Conference Paper, Proceedings of the 2010 conference on Uncertainty in Artificial Intelligence Presented at: Conference on Uncertainty in Artificial Intelligence, held on Santa Catalina Island, CA, USA from July 8th - July 11th, 2010 Authors: Matthias Broecheler, Lilyana Mihalkova, Lise Getoor Direct link to paper Data set used in the experiments Abstract Many machine learning applications ... http://www.knowledgefrominformation.com/2010/07/08/probabilistic-similarity-logic/ COSI, our cloud-oriented graph database framework for fast subgraph identification, has received some attention in the media. So far, I have found two articles on the internet (1, 2) which are based on the original press release and additional interviews. http://www.knowledgefrominformation.com/2010/07/02/cosi-press-coverage/