dragon.ir.clustering

Interface Clustering

All Known Implementing Classes:

AbstractClustering, BasicKMean, BisectKMean, HierClustering, LinkKMean

public interface Clustering

Interface of text clustering method

Copyright: Copyright (c) 2005

Company: IST, Drexel University

Version:

1.0

Author:

Davis Zhou

Method Summary

Modifier and Type	Method and Description
boolean	cluster() Cluster all documents in the index reader to the given number of clusters
boolean	cluster(IRDoc[] arrDoc) Cluster given testing documents to the given number of clusters
DocCluster	getCluster(int index) One should call the cluster method before calling this method.
int	getClusterNum()
DocClusterSet	getClusterSet() One should call the cluster method before calling this method.
FeatureFilter	getFeatureFilter()
IndexReader	getIndexReader()
long	getRandomSeed()
void	setFeatureFilter(FeatureFilter featureFilter)
void	setRandomSeed(long seed)

Method Detail

getClusterNum

int getClusterNum()

Returns:

the number of clusters

getRandomSeed

long getRandomSeed()

setRandomSeed

void setRandomSeed(long seed)

getClusterSet

DocClusterSet getClusterSet()

One should call the cluster method before calling this method.

Returns:

all clusters

getCluster

DocCluster getCluster(int index)

One should call the cluster method before calling this method.

Parameters:

index - the index of the cluster of interest

Returns:

the given cluster

getIndexReader

IndexReader getIndexReader()

Returns:

the index reader the clustering method is working on

cluster

boolean cluster()

Cluster all documents in the index reader to the given number of clusters

Returns:

true if clustering successfully

cluster

boolean cluster(IRDoc[] arrDoc)

Cluster given testing documents to the given number of clusters

Parameters:

arrDoc - the document set for clustering

Returns:

true if clustering successfully

getFeatureFilter

FeatureFilter getFeatureFilter()

setFeatureFilter

void setFeatureFilter(FeatureFilter featureFilter)