cluster
Interface ClusterDoc

All Superinterfaces:

java.lang.Comparable<ClusterDoc>

All Known Implementing Classes:

ClusterableReuters, KnownDoc, SearchResultDoc, TestDoc, TestReuters

public interface ClusterDoc
extends java.lang.Comparable<ClusterDoc>

Represents a document that I can conduct unsupervised clustering on.
In fact, pretty much all documents can undergo this process if they implement these methods.
These documents also need to be able to compare themselves (for sorting purposes)

Author:

davidc

Method Summary

void	addTermSetCount(Phrase termSet, int n) This document should record how frequently this termSet occured
void	checkSourceExists() Throw an exception if this file won't be cluster-able
void	destroyLocalDoc() After finding how often all the phrases are in this doc, this method should allow the supporting document to be released to free up memory.
java.lang.String[][]	getFixedWordSentences() Each String should be fixed by VectorManager before being returned
int[][]	getIdxSentences(VectorManager vm) Each entry represents the integer.
int	getNumInstancesOfTermSet(Phrase s) Each document should get a unique id
java.lang.String[][]	getSentences()
double	getTermSetsSupported()
boolean	isJunkPhrase(java.lang.String w) Added to allow differentiation between phrases of scientific articles and general search results
void	loadWindowedDoc() Initially, the idea was to support proximity windows (eg.

Methods inherited from interface java.lang.Comparable

compareTo

Method Detail

getTermSetsSupported

double getTermSetsSupported()

getNumInstancesOfTermSet

int getNumInstancesOfTermSet(Phrase s)

Each document should get a unique id

Returns:

addTermSetCount

void addTermSetCount(Phrase termSet,
                     int n)

This document should record how frequently this termSet occured

Parameters:

termSet -

n -

isJunkPhrase

boolean isJunkPhrase(java.lang.String w)

Added to allow differentiation between phrases of scientific articles and general search results

Parameters:

w - Space-separated words

Returns:

checkSourceExists

void checkSourceExists()
                       throws java.io.FileNotFoundException

Throw an exception if this file won't be cluster-able

Throws:

java.io.FileNotFoundException

getFixedWordSentences

java.lang.String[][] getFixedWordSentences()
                                           throws java.io.FileNotFoundException,
                                                  java.io.IOException

Each String should be fixed by VectorManager before being returned

Returns:

Throws:

java.io.FileNotFoundException

java.io.IOException

getIdxSentences

int[][] getIdxSentences(VectorManager vm)

Each entry represents the integer. This method possibly allows PhraseFinder to save time while finding frequent phrases.
Notice that the dimensions returned here should be exactly the same as those returned in getFixedWordSentences()

Parameters:

vm -

Returns:

getSentences

java.lang.String[][] getSentences()
                                  throws java.io.FileNotFoundException,
                                         java.io.IOException

Throws:

java.io.FileNotFoundException

java.io.IOException

loadWindowedDoc

void loadWindowedDoc()

Initially, the idea was to support proximity windows (eg. phrases of 5 words excluding stopwords) but just using each sentence as a window yields good results with much better performance.

Throws:

java.io.FileNotFoundException

java.io.IOException

destroyLocalDoc

void destroyLocalDoc()

After finding how often all the phrases are in this doc, this method should allow the supporting document to be released to free up memory.