Learn More
How closely related are two nodes in a graph? How to compute this score quickly, on huge, disk-resident, real graphs? Random walk with restart (RWR) provides a good relevance score between two nodes in a weighted graph, and it has been successfully used in numerous settings, like automatic captioning of images, generalizations to the "connection subgraphs",(More)
Given an image (or video clip, or audio song), how do we automatically assign keywords to it? The general problem is to find correlations across the media in a collection of multimedia objects like video clips, with colors, and/or motion, and/or audio, and/or text scripts. We propose a novel, graph-based approach, "MMG", to discover such cross-modal(More)
Much of the motion capture data used in animations, commercials, and video games is carefully segmented into distinct motions either at the time of capture or by hand after the capture session. As we move toward collecting more and longer motion sequences, however, automatic segmentation techniques will become important for processing the results in a(More)
How closely related are two nodes in a graph? How to compute this score quickly, on huge, disk-resident, real graphs? Random walk with restart (RWR) provides a good relevance score between two nodes in a weighted graph, and it has been successfully used in numerous settings, like automatic captioning of images, generalizations to the “connection subgraphs”,(More)
* This material is based upon work supported by the National Science Foundation under Grants No. IRI-9817496, IIS-9988876, IIS-0113089, IIS-0209107, IIS-0205224, INT-0318547, SENSOR-0329549, EF-0331657, by the Pennsylvania Infrastructure Technology Alliance (PITA) Grant No. 22-901-0001, and by the Defense Advanced Research Projects Agency under Contract No.(More)
Given an image, how do we automatically assign keywords to it? In this paper, we propose a novel, graph-based approach (GCap) which outperforms previously reported methods for automatic image captioning. Moreover, it is fast and scales well, with its training and testing time linear to the data set size. We report auto-captioning experiments on the(More)
We present FEMine, an automatic system for image-based gene expression analysis. We perform experiments on the largest publicly available collection of Drosophila ISH (<i>in situ</i> hybridization) images, showing that our FEMine system achieves excellent performance in classification, clustering, and content-based image retrieval. The major innovation of(More)
Current applications have produced graphs on the order of hundreds of thousands of nodes and millions of edges. To take advantage of such graphs, one must be able to find patterns, outliers, and communities. These tasks are better performed in an interactive environment, where human expertise can guide the process. For large graphs, though, there are some(More)
Given a large collection of medical images of several conditions and treatments, how can we succinctly describe the characteristics of each setting? For example, given a large collection of retinal images from several different experimental conditions (normal, detached, reattached, etc.), how can data mining help biologists focus on important regions in the(More)