dragon.ir.clustering.clustermodel

Interface ClusterModel

All Known Implementing Classes:

AbstractClusterModel, CosineClusterModel, EuclideanClusterModel, MultinomialClusterModel

public interface ClusterModel

Interface of cluster model which compute the distance between a document and a document cluster

Copyright: Copyright (c) 2005

Company: IST, Drexel University

Version:

1.0

Author:

Davis Zhou

Method Summary

Modifier and Type	Method and Description
int	getClusterNum()
double	getDistance(IRDoc doc, DocCluster cluster)
double	getDistance(IRDoc doc, int clusterNo)
FeatureFilter	getFeatureFilter()
void	setClusterNum(int clusterNum)
void	setDocCluster(DocCluster cluster) Iterative partional approaches (e.g.
void	setDocClusters(DocClusterSet clusterSet) This method is equal to calling the setDocCluster method for all clusters.
void	setFeatureFilter(FeatureFilter filter) A feature selector is set.

Method Detail

getDistance

double getDistance(IRDoc doc,
                   DocCluster cluster)

Parameters:

doc - the document

cluster - the document cluster

Returns:

the distance between the document and the cluster

getDistance

double getDistance(IRDoc doc,
                   int clusterNo)

setDocCluster

void setDocCluster(DocCluster cluster)

Iterative partional approaches (e.g. K-Means) need to re-compute the cetroid of each cluster after each iteration. This method gives the chance to re-compute the centroid.

Parameters:

cluster - the new cluster

setDocClusters

void setDocClusters(DocClusterSet clusterSet)

This method is equal to calling the setDocCluster method for all clusters.

Parameters:

clusterSet - all new clusters

getClusterNum

int getClusterNum()

setClusterNum

void setClusterNum(int clusterNum)

Parameters:

clusterNum - the number of clusters

setFeatureFilter

void setFeatureFilter(FeatureFilter filter)

A feature selector is set. After that, the excluded features do not count in cluster model any more.

Parameters:

selector - the feature selector

getFeatureFilter

FeatureFilter getFeatureFilter()

Returns:

the feature selector used for the cluster model