@conference {16894,
	title = {Depth-first k-nearest neighbor finding using the MaxNearestDist estimator},
	booktitle = {Image Analysis and Processing, 2003.Proceedings. 12th International Conference on},
	year = {2003},
	month = {2003/09//},
	pages = {486 - 491},
	abstract = {Similarity searching is an important task when trying to find patterns in applications which involve mining different types of data such as images, video, time series, text documents, DNA sequences, etc. Similarity searching often reduces to finding the k nearest neighbors to a query object. A description is given of how to use an estimate of the maximum possible distance at which a nearest neighbor can be found to prune the search process in a depth-first branch-and-bound k-nearest neighbor finding algorithm. Using the MaxNearestDist estimator (Larsen, S. and Kanal, L.N., 1986) in the depth-first k-nearest neighbor algorithm provides a middle ground between a pure depth-first and a best-first k-nearest neighbor algorithm.},
	keywords = {branch-and-bound, data, depth-first, distance;, DNA, documents;, estimation;, estimator;, finding;, images;, k-nearest, matching;, maximum, MaxNearestDist, mining;, neighbor, parameter, pattern, possible, process;, processing;, query, search, searching;, sequences;, series;, similarity, text, TIME, tree, video;},
	doi = {10.1109/ICIAP.2003.1234097},
	author = {Samet, Hanan}
}
@conference {12306,
	title = {Scalable peer finding on the Internet},
	booktitle = {Global Telecommunications Conference, 2002. GLOBECOM {\textquoteright}02. IEEE},
	volume = {3},
	year = {2002},
	month = {2002/11//},
	pages = {2205 - 2209 vol.3 - 2205 - 2209 vol.3},
	abstract = {We consider the problem of finding nearby application peers over the Internet. We define a new peer-finding scheme (called Tiers) that scales to large application peer groups. Tiers creates a hierarchy of the peers, which allows an efficient and scalable solution to this problem. The scheme can be implemented entirely in the application-layer and does not require the deployment of either any additional measurement services, or well-known reference landmarks in the network. We present detailed evaluation of Tiers and compare it to one previously proposed scheme called Beaconing. Through analysis and detailed simulations on 10,000 node Internet-like topologies we show that Tiers achieves comparable or better performance with a significant reduction in control overheads for groups of size 32 or more.},
	keywords = {application, application-layer;, Beaconing;, CONTROL, finding;, Internet-like, Internet;, measurement, network, overhead, peer, peer-finding, peers;, protocol;, protocols;, reduction;, scalable, scheme;, services;, simulations;, solution;, Tiers;, topologies;, topology;},
	doi = {10.1109/GLOCOM.2002.1189023},
	author = {Banerjee,S. and Kommareddy,C. and Bhattacharjee, Bobby}
}
