Similarity	Concept
	Information retrieval definition
	Document clustering
	Operational information retrieval
	Automatic document classification
	Experimental information retrieval
	Cluster based retrieval
	Automatic classification
	Clustering
	Cluster methods
	Information structure

Pages with this concept

Similarity	Page	Snapshot
	52	have to be made of the file of object descriptions ...1 the object descriptions are processed serially;2 the first object becomes the cluster representative of the first cluster;3 each subsequent object is matched against all cluster representatives existing at its processing time;4 a given object is assigned to one cluster or more if overlap is allowed according to some condition on the matching function;5 when an object is assigned to a cluster the representative for that cluster is recomputed;6 if an object fails a certain test it becomes the cluster representative of a new cluster ...Once again the final classification is dependent on input parameters which can only be determined empirically and which are likely to be different for different sets of objects and must be specified in advance ...The simplest version of this kind of algorithm is probably one due to Hill [37]...Related to the single pass approach is the algorithm of MacQueen [41]which starts with an arbitrary initial partition of the objects ...A third type of algorithm is represented by the work of Dattola [42]...
	51	restricting the number of clusters and by bounding the size of each cluster ...Rather than give a detailed account of all the heuristic algorithms,I shall instead discuss some of the main types and refer the reader to further developments by citing the appropriate authors ...The most important concept is that of cluster representative variously called cluster profile,classification vector,or centroid ...1 the number of clusters desired;2 a minimum and maximum size for each cluster;3 a threshold value on the matching function,below which an object will not be included in a cluster;4 the control of overlap between clusters;5 an arbitrarily chosen objective function which is optimised ...Almost all of the algorithms are iterative,i ...Probably the most important of this kind of algorithm is Rocchio s clustering algorithm [36]which was developed on the SMART project ...Most of these algorithms aim at reducing the number of passes that