The cost structure of sensemaking
CHI '93 Proceedings of the INTERACT '93 and CHI '93 Conference on Human Factors in Computing Systems
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Understanding belief propagation and its generalizations
Exploring artificial intelligence in the new millennium
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Signpost from the masses: learning effects in an exploratory social tag search browser
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
SNARE: a link analytic system for graph labeling and risk detection
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
“Search, Show Context, Expand on Demand”: Supporting Large Graph Exploration with Degree-of-Interest
IEEE Transactions on Visualization and Computer Graphics
Apolo: making sense of large network data by combining rich user interaction and machine learning
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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We present APOLO, a system that uses a mixed-initiative approach to help people interactively explore and make sense of large network datasets. It combines visualization, rich user interaction and machine learning to engage the user in bottom-up sensemaking to gradually build up an understanding over time by starting small, rather than starting big and drilling down. APOLO helps users find relevant information by specifying exemplars, and then using a machine learning method called Belief Propagation to infer which other nodes may be of interest. We demonstrate APOLO's usage and benefits using a Google Scholar citation graph, consisting of 83,000 articles (nodes) and 150,000 citations relationships. A demo video of APOLO is available at http://www.cs.cmu.edu/~dchau/apolo/apolo.mp4.