Collective Classification of Network Data
University of MarylandCollege Park, MD 20742 email@example.com
University of MarylandCollege Park, MD 20742 getoor@;cs.umd.edu
Network data has become ubiquitous. Communication networks, social networks, and the World Wide Web are becoming increasingly important to our day-to-day life. Moreover, networks can be defined implicitly by certain structured data sources, such as images and text. We are often interested in inferring hidden attributes (i.e., labels) about network data, such as whether a Facebook user will adopt a product, or whether a pixel in an image is part of the foreground, background, or some specific object. Intuitively, the network ...