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between the algorithms of Rocchio,Rieber and Marathe,Bonner see below and his own
...One further algorithm that should be mentioned here is that due to Litofsky [28]...Finally,the Bonner [45]algorithm should be mentioned
...The major advantage of the algorithmically defined cluster methods is their speed:order n log n where n is the number of objects to be clustered compared with order n 2 for the methods based on association measures
...One obvious omission from the list of cluster methods is the group of mathematically or statistically based methods such as Factor Analysis and Latest Class Analysis
...The method of single link avoids the disadvantages just mentioned
...Single link The dissimilarity coefficient is the basic input to a single link clustering algorithm
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The second criterion for choice is the efficiency of the clustering process in terms of speed and storage requirements
...Efficiency is really a property of the algorithm implementing the cluster method
...In the main,two distinct approaches to clustering can be identified:1 the clustering is based on a measure of similarity between the objects to be clustered;2 the cluster method proceeds directly from the object descriptions
...The most obvious examples of the first approach are the graph theoretic methods which define clusters in terms of a graph derived from the measure of similarity
...A string is a connected sequence of objects from some starting point
...A connected component is a set of objects such that each object is connected to at least one other member of the set and the set is maximal with respect to this property
...A maximal complete subgraph is a subgraph such that each node is connected to every other node in the subgraph and the set is maximal with respect to this property,i
...node were included anywhere the completeness condition would be violated
...A large class of hierarchic cluster methods is based on the initial measurement of similarity
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