de.aitools.dm.clusterlabeling.algorithms
Class ASoftClusterLabeler

java.lang.Object
  extended by de.aitools.dm.clustering.algorithms.ASoftClusterer
      extended by de.aitools.dm.clusterlabeling.algorithms.ASoftClusterLabeler
All Implemented Interfaces:
SoftClusterer, ClusterLabeler
Direct Known Subclasses:
ACarrot2ClusterLabeler

public abstract class ASoftClusterLabeler
extends ASoftClusterer
implements ClusterLabeler

Version:
$Id: ASoftClusterLabeler.java,v 1.1 2011/07/18 15:51:21 hoppe Exp $
Author:
dennis.hoppe(/\t)uni-weimar.de

Constructor Summary
ASoftClusterLabeler()
          Default constructor.
 
Method Summary
abstract  int[][] clusterSoft(java.lang.String[] data)
          Clusters the input data.
 java.lang.String[] getClusterLabels()
          Returns the label(s) for each cluster.
 
Methods inherited from class de.aitools.dm.clustering.algorithms.ASoftClusterer
clusterSoft, clusterSoft, clusterSoft, clusterSoft, getBiggestRange
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

ASoftClusterLabeler

public ASoftClusterLabeler()
Default constructor.

Method Detail

getClusterLabels

public java.lang.String[] getClusterLabels()
Returns the label(s) for each cluster.

Specified by:
getClusterLabels in interface ClusterLabeler
Returns:
an array of cluster labels

clusterSoft

public abstract int[][] clusterSoft(java.lang.String[] data)
Clusters the input data. Be aware that some cluster labeling algorithms such as Lingo perform their own tokenization. Thus, you should not perform stopword removal and stemming prior to calling clusterSoft(String[]).

Parameters:
data - input as text documents
Returns:
the clustering of input texts as an 2d-array