Similar concepts
Pages with this concept
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A and B are two clusters
...that their corresponding documents are less dissimilar than some specified level of dissimilarity
...Let us now look at other ways of representing clusters
...where Di is usually the Euclidean norm,i
...More often than not the documents are not represented by numerical vectors but by binary vectors or equivalently,sets of keywords
...remember n is the number of documents in the cluster by the following procedure
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differences in the scale and in the use to which a classification structure is to be put
...In the case of scale,the size of the problem in IR is invariably such that for cluster methods based on similarity matrices it becomes impossible to store the entire similarity matrix,let alone allow random access to its elements
...When a classification is to be used in IR,it affects the design of the algorithm to the extent that a classification will be represented by a file structure which is 1 easily updated;2 easily searched;and 3 reasonably compact
...Only 3 needs some further comment
...Conclusion Let me briefly summarise the logical structure of this chapter
...This chapter ended on a rather practical note
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