Intelligent desktop assistants could provide more help for users if they could learn models of the users’ workflows. However, discovering desktop workflows is difficult becau...
Jianqiang Shen, Erin Fitzhenry, Thomas G. Dietteri...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
In this paper, we present a technique for visual analysis of documents based on the semantic representation of text in the form of a directed graph, referred to as semantic graph....
Delia Rusu, Blaz Fortuna, Dunja Mladenic, Marko Gr...
—This paper reports on experience gained and lessons learned from an intensive investigation of model-driven engineering methodology and technology for application to high-integr...
Abstract— Motivated by applications in cryptography, we consider a generalization of randomness extraction and the related notion of privacy amplification to the case of two cor...