@conference {17442,
	title = {TreeVersity: Comparing tree structures by topology and node{\textquoteright}s attributes differences},
	booktitle = {2011 IEEE Conference on Visual Analytics Science and Technology (VAST)},
	year = {2011},
	month = {2011/10/23/28},
	pages = {275 - 276},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {It is common to classify data in hierarchies, they provide a comprehensible way of understanding big amounts of data. From budgets to organizational charts or even the stock market, trees are everywhere and people find them easy to use. However when analysts need to compare two versions of the same tree structure, or two related taxonomies, the task is not so easy. Much work has been done on this topic, but almost all of it has been restricted to either compare the trees by topology, or by the node attribute values. With this project we are proposing TreeVersity, a framework for comparing tree structures, both by structural changes and by differences in the node attributes. This paper is based on our previous work on comparing traffic agencies using LifeFlow [1, 2] and on a first prototype of TreeVersity.},
	keywords = {Computer science, data classification, Data visualization, Educational institutions, hierarchy, Image color analysis, LifeFlow, node attributes differences, Pattern classification, structural changes, Topology, topology attributes differences, traffic agencies, tree structures comparison, trees (mathematics), TreeVersity, Vegetation, Visualization},
	isbn = {978-1-4673-0015-5},
	doi = {10.1109/VAST.2011.6102471},
	author = {Gomez,J.A.G. and Buck-Coleman,A. and Plaisant, Catherine and Shneiderman, Ben}
}
@article {12285,
	title = {Efficient peer location on the Internet},
	journal = {Computer Networks},
	volume = {45},
	year = {2004},
	month = {2004/05/15/},
	pages = {5 - 17},
	abstract = {We consider the problem of locating nearby application peers over the Internet. We define a new peer-location scheme (called Tiers), that scales to large application peer groups. Tiers creates a hierarchy of peers, and provides an efficient and scalable solution to the peer-location problem. Tiers can be implemented entirely in the application-layer and does not require the deployment of either any additional measurement services, or well-known reference points in the network.We have evaluated the performance of Tiers through detailed experiments. Our results show that Tiers is able to locate the nearest peers quickly (<<1 s) and accurately on wide-area Internet-like topologies. We have also compared the performance of Tiers with two other schemes, Beaconing and Distributed Binning, both of which are known to have good performance. Both these techniques are reference-points based schemes and are efficient for overlays with a small number of peers (e.g. ⩽32). Our results show that Tiers significantly outperforms both these schemes. Tiers is particularly efficient for large overlay networks, has an order of magnitude lower control overhead for overlays with 512 peers and still achieves greater accuracy in locating the nearest peers.
},
	keywords = {Group communication, hierarchy, overlays, Peer location, triangle inequality},
	isbn = {1389-1286},
	doi = {10.1016/j.comnet.2004.02.005},
	url = {http://www.sciencedirect.com/science/article/pii/S1389128604000271},
	author = {Banerjee,Suman and Kommareddy,Chris and Bhattacharjee, Bobby}
}
@conference {12686,
	title = {Robust Bayesian cameras motion estimation using random sampling},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1361 - 1364 Vol.2 - 1361 - 1364 Vol.2},
	abstract = {In this paper, we propose an algorithm for robust 3D motion estimation of wide baseline cameras from noisy feature correspondences. The posterior probability density function of the camera motion parameters is represented by weighted samples. The algorithm employs a hierarchy coarse-to-fine strategy. First, a coarse prior distribution of camera motion parameters is estimated using the random sample consensus scheme (RANSAC). Based on this estimate, a refined posterior distribution of camera motion parameters can then be obtained through importance sampling. Experimental results using both synthetic and real image sequences indicate the efficacy of the proposed algorithm.},
	keywords = {3D, baseline, Bayesian, CAMERAS, cameras;, coarse-to-fine, consensus, density, estimation;, feature, function;, hierarchy, image, images;, importance, matching;, MOTION, posterior, probability, probability;, processing;, random, RANSAC;, real, realistic, sample, sampling;, scheme;, sequences;, stereo, strategy;, synthetic, wide},
	doi = {10.1109/ICIP.2004.1419754},
	author = {Qian, G. and Chellapa, Rama and Qinfen Zheng}
}
@article {12309,
	title = {Scalable application layer multicast},
	journal = {SIGCOMM Comput. Commun. Rev.},
	volume = {32},
	year = {2002},
	month = {2002/08//},
	pages = {205 - 217},
	abstract = {We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data delivery trees with desirable properties.We present extensive simulations of both our protocol and the Narada application-layer multicast protocol over Internet-like topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25\%), improved or similar end-to-end latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic.Finally, we present results from our wide-area testbed in which we experimented with 32-100 member groups distributed over 8 different sites. In our experiments, average group members established and maintained low-latency paths and incurred a maximum packet loss rate of less than 1\% as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100.},
	keywords = {application layer multicast, hierarchy, overlay networks, peer-to-peer systems, scalability},
	isbn = {0146-4833},
	doi = {10.1145/964725.633045},
	url = {http://doi.acm.org/10.1145/964725.633045},
	author = {Banerjee,Suman and Bhattacharjee, Bobby and Kommareddy,Christopher}
}
@conference {17501,
	title = {Visualizing digital library search results with categorical and hierarchical axes},
	booktitle = {Proceedings of the fifth ACM conference on Digital libraries},
	series = {DL {\textquoteright}00},
	year = {2000},
	month = {2000///},
	pages = {57 - 66},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Digital library search results are usually shown as a textual list,    with 10-20 items per page. Viewing several thousand search results at once on a two-dimensional display with continuous variables is a promising       alternative. Since these displays can overwhelm some users, we created a    simplified two-dimensional display that uses categorical and hierarchical   axes, called hieraxes. Users appreciate the meaningful and limited number   of terms on each hieraxis. At each grid point of the display we show a      cluster of color-coded dots or a bar chart. Users see the entire result set and can then click on labels to move down a level in the hierarchy.         Handling broad hierarchies and arranging for imposed hierarchies led to     additional design innovations. We applied hieraxes to a digital video   library of science topics used by middle school teachers, a legal   information system, and a technical library using the ACM Computing Classification System. Feedback from usability testing with 32 subjects revealed strengths and weaknesses.},
	keywords = {categorical axes, digital libraries, Graphical user interfaces, hierarchy, hieraxes, Information Visualization},
	isbn = {1-58113-231-X},
	doi = {10.1145/336597.336637},
	url = {http://doi.acm.org/10.1145/336597.336637},
	author = {Shneiderman, Ben and Feldman,David and Rose,Anne and Grau,Xavier Ferr{\'e}}
}
@conference {17962,
	title = {Skip Strips: maintaining triangle strips for view-dependent rendering},
	booktitle = {Visualization {\textquoteright}99. Proceedings},
	year = {1999},
	month = {1999/10//},
	pages = {131 - 518},
	abstract = {View-dependent simplification has emerged as a powerful tool for graphics acceleration in visualization of complex environments. However, view-dependent simplification techniques have not been able to take full advantage of the underlying graphics hardware. Specifically, triangle strips are a widely used hardware-supported mechanism to compactly represent and efficiently render static triangle meshes. However, in a view-dependent framework, the triangle mesh connectivity changes at every frame, making it difficult to use triangle strips. We present a novel data structure, Skip Strip, that efficiently maintains triangle strips during such view-dependent changes. A Skip Strip stores the vertex hierarchy nodes in a skip-list-like manner with path compression. We anticipate that Skip Strips will provide a road map to combine rendering acceleration techniques for static datasets, typical of retained-mode graphics applications, with those for dynamic datasets found in immediate-mode applications.},
	keywords = {(computer, Acceleration, acceleration;graphics, applications;path, applications;skip-list-like, changes;view-dependent, compression;rendering, connectivity;triangle, data, datasets;graphics, datasets;static, environments;data, equipment;data, graphic, Graphics, graphics);spatial, hardware;hardware-supported, hierarchy, manner;static, mechanism;immediate-mode, mesh, meshes;triangle, nodes;view-dependent, rendering;view-dependent, simplification;visualization;computer, Skip, Strips;complex, strips;vertex, structure;dynamic, structures;, techniques;retained-mode, triangle, visualisation;rendering},
	doi = {10.1109/VISUAL.1999.809877},
	author = {El-Sana,J. and Azanli,E. and Varshney, Amitabh}
}
