The document describes experimental results from running fuzzy c-means clustering with simulated annealing (FuzzyCmeansSA) and k-means clustering algorithms. It reports the following: - FuzzyCmeansSA had an execution time of 2.098129553 and memory of 27.55. - KMeansClustering had a longer execution time of 22.37031143 but better memory usage of 65.742966. - The code implements the two algorithms and inserts performance results into database tables for analysis.

1. Experimental Results:
 Execution time
Time is defined as the fraction of relevant instances that are retrieved. In other words
it is said as the number of correctly predicted on better execution time .the time is carried
out using equation 4.3.
TIME=TP/TP+FN ……………….. (4.3)
 Memory :
Memory is defined as the number of correctly predicted on the better instances
divided by the total number of instances present in dataset and the memory is
calculated using equation 4.4.
MEMORY=TP+TN/TP+TN+FP+FN ……………(4.4)

2. Screenshot:

16. AlgorithmName Execution Time
FuzzyCmeansSA 2.098129553
KMeansClustering 22.37031143
The comparisonratiois measuredusingthe execution time;the fuzzycmeansandK-means
clustering.the K–meansperformsbetterexecutiontime.

17. AlgorithmName Memory
FuzzyCmeansSA 27.55
KMeansClustering 65.742966
The comparisonratiois measuredusingthe memory;the fuzzycmeansandK-meansclustering.the
K–meansperformsbettermemory.

18. Coding:
NLP_Process.java
/*
* To change thistemplate,choose Tools|Templates
* and openthe template inthe editor.
*/
package conceptdrivenclustering;
importCom.commonfiles.db_conn;
importedu.stanford.nlp.ling.HasWord;
importedu.stanford.nlp.ling.Sentence;
importedu.stanford.nlp.ling.TaggedWord;
importedu.stanford.nlp.tagger.maxent.MaxentTagger;
importjava.io.StringReader;
importjava.sql.ResultSet;
importjava.sql.*;
importjava.util.ArrayList;
importjava.util.List;
importjava.util.Vector;
importjava.util.logging.Level;

19. importjava.util.logging.Logger;
/**
*
* @author admini
*/
publicclassNLP_Process {
publicstaticvoidmain(Stringargs[]) {
try {
db_conndb = newdb_conn();
db.st.executeUpdate("truncate table tbl_Nlpprocess");
Vectorvstopword=newVector();
Stringsel1= "select*from stopwords";
ResultSetrset1= db.stat1.executeQuery(sel1);
while (rset1.next()) {
vstopword.add(rset1.getString(2));
}
Vectorvfilename =newVector();
Vectorvfilecontent=newVector();
Vectorvcomment= newVector();

20. //Vectorvdomain= newVector();
Stringsel_qry= "selectfilename,filecontentfromtbl_stopwordremoval;";
ResultSetrset=db.st.executeQuery(sel_qry);
while (rset.next()) {
Stringcomm = "";
Stringtitle = rset.getString(1);
vfilename.add(title);
Stringfilecontent=rset.getString(2);
// Stringdomain= rset.getString(3);
// vdomain.add(domain);
Stringcommentsarr[] =filecontent.split("");
for (intk= 0; k < commentsarr.length;k++) {
Stringword = commentsarr[k];
// out.println(word);
booleanflag= false;
for (intx = 0; x < vstopword.size();x++) {
if (word.trim().equalsIgnoreCase(vstopword.get(x).toString().trim())) {
flag= true;
}

21. }
if (flag== true) {
} else {
MaxentTaggertagger= new MaxentTagger("D:/left3words-wsj-0-18.tagger");
@SuppressWarnings("unchecked")
StringstringToBeParsed=word;
StringReaderreader=newStringReader(stringToBeParsed);
List<List<HasWord>>sentences=tagger.tokenizeText(reader); //new
BufferedReader(new FileReader("testdata.txt")));
for(List<HasWord>sentence :sentences) {
ArrayList<TaggedWord>tSentence=tagger.tagSentence(sentence);
Stringstr = Sentence.listToString(tSentence,false);
//System.out.println(str);
Stringstr1[] = str.split("");
for (inti = 0; i < str1.length;i++) {
// System.out.println("------"+ str1[i].toString());
if (str1[i].toString().contains("/NN")) {
comm = comm+ word+ " ";
}//jj //jjr
if (str1[i].toString().contains("/JJ")) {

22. comm = comm+ word+ " ";
}
if (str1[i].toString().contains("/JJR")) {
comm = comm+ word+ " ";
}
if (str1[i].toString().contains("/NNP")) {
comm = comm+ word+ " ";
}
}
}
}
}
Stringinsert_qry= "insertintotbl_Nlpprocessvalues('"+title + "','" + filecontent+"','" +
comm + "')";
//System.out.println("---"+insert_qry);
db.stat4.executeUpdate(insert_qry);
vcomment.add(comm);
}
} catch (Exceptionex) {
Logger.getLogger(NLP_Process.class.getName()).log(Level.SEVERE,null,ex);
}
}
}

23. FuzzyCmeansClustering.java
/*
* To change thistemplate,choose Tools|Templates
* and openthe template inthe editor.
*/
package clustering;
importCom.commonfiles.db_conn;
importCom.commonfiles.tableview1;
importjava.sql.*;
importjava.util.*;
/**
*
* @author Lap1
*/
publicclassFuzzyCmeansandSimulatedannealing{
publicstaticvoidmain(Stringargs[])
{
db_conndb=newdb_conn();

24. try {
double starttime1= System.nanoTime();
Runtime run= Runtime.getRuntime();
double free =run.freeMemory();
double total = run.totalMemory();
double max = run.maxMemory();
double used=total - free;
db.st.executeUpdate("truncate table tbl_cluster_fcmsa");
intcount = 0;
Stringsel_qry_sum= "selectcontents,count(wc) fromtbl_weight";
ResultSetrset22= db.st1.executeQuery(sel_qry_sum);
while (rset22.next()){
count = Integer.parseInt(rset22.getString(2));
}
intheat=5;

25. intcool=5;
intfmemberfun=0;
intmax1 = 0;
intmin = 0;
Vectorvc = newVector();
Stringsel_qry= "selectcontents,Max(wc) fromtbl_weight orderbywc";
System.out.println(sel_qry);
ResultSetrset1= db.st2.executeQuery(sel_qry);
while (rset1.next()){
max1 = Integer.parseInt(rset1.getString(2));
}
Stringsel_qry1= "selectcontents,Min(wc) fromtbl_weightorderbywc";
ResultSetrset2= db.st3.executeQuery(sel_qry1);
while (rset2.next()){
min = Integer.parseInt(rset2.getString(2));
}

26. //Mean-Max Membership
intfcenter= max1/2 + min/ 2 ;
System.out.println("------FuzzyCenter-------"+fcenter);
Stringsel_qry2= "select*from tbl_weightwhere wc>='" + (fcenter+heat) +"'
orderby wc";
System.out.println(sel_qry2);
ResultSetrset3= db.st3.executeQuery(sel_qry2);
while (rset3.next()){
String tags= rset3.getString(1);
tags = tags.replace("'","");
tags = tags.replace(",","");
String contents=rset3.getString(2);
//disease =disease.replace("'","");
//disease =disease.replace(",","");
String insert_Qry= "insertintotbl_cluster_fcmsavalues('"+tags + "','" +
contents+ "','" + rset3.getString(3) +"','" + rset3.getString(4) +"', '2' )";
System.out.println(insert_Qry);
db.sta.executeUpdate(insert_Qry);
}
Stringsel_qry4= "select*from tbl_weightwhere wc<='" + (fcenter+heat) + "'
orderby wc";

27. System.out.println(sel_qry4);
ResultSetrset5= db.st2.executeQuery(sel_qry4);
while (rset5.next()){
String tags= rset5.getString(1);
tags = tags.replace("'","");
tags = tags.replace(",","");
String contents=rset5.getString(2);
//disease =disease.replace("'","");
//disease =disease.replace(",","");
String insert_Qry= "insertintotbl_cluster_fcmsavalues('"+tags + "','" +
contents+ "','" + rset5.getString(3) +"','" + rset5.getString(4) +"','1' )";
System.out.println(insert_Qry);
db.stat4.executeUpdate(insert_Qry);
}
Runtime run1= Runtime.getRuntime();
double free1= run1.freeMemory();
double total1= run1.totalMemory();
double used1= total1- free1;

28. double total_exememrory=used1- used;
floatumemory= (float) total_exememrory/1024/10;
System.out.println("-UsedMemory--"+umemory);
double Endtime =System.nanoTime();
double ExeTime =(Endtime - starttime1) /60 / 60/10;
System.out.println("Total ExecutionTime "+ExeTime/10000);
Stringinsert_performence="insertintotbl_performence_fcmvalues( 'Fuzzy CmeansSA ',
'ExecutionTime','"+Math.abs(ExeTime )/10000+"') ";
db.st.executeUpdate(insert_performence);
Stringinsert_performence1="insertintotbl_performence_fcmvalues( 'FuzzyCmeansSA ',
'Memory', '"+Math.abs(umemory)+"') ";

29. db.st2.executeUpdate(insert_performence1);
tableview1tv=newtableview1();
tv.table("select*fromtbl_cluster_fcmsa","FuzzyCmeansClusterandSA");
} catch (Exceptionexpp) {
expp.printStackTrace();
}
}
}
Kmeans_Clustering.java
/*
* To change thistemplate,choose Tools|Templates
* and openthe template inthe editor.
*/
package clustering;
importCom.commonfiles.db_conn;
importCom.commonfiles.tableview1;
importjava.sql.*;
/**
*

30. * @author Lap1
*/
publicclassClustering{
publicstaticvoidmain(Stringargs[])
{
db_conndb=newdb_conn();
try{
double starttime1= System.nanoTime();
Runtime run= Runtime.getRuntime();
double free =run.freeMemory();
double total = run.totalMemory();
double maxmem=run.maxMemory();
double used=total - free;
ResultSetrset=db.sta1.executeQuery("select*fromtbl_weight");
while(rset.next())
{
Stringfilename=rset.getString(1);
Stringfilecontents=rset.getString(2);

31. Stringtags=rset.getString(3);
intwc=Integer.parseInt(rset.getString(4));
}
intmax=0;
Stringsel_max="Selectmax(wc) fromtbl_weight";
ResultSetrset1=db.stat4.executeQuery(sel_max);
while(rset1.next())
{
max=Integer.parseInt(rset1.getString(1));
}
intnoofcluster=4;
intstart=0;
intend=max/4;
for(inti=0;i<noofcluster;i++)
{

32. Stringsel_qry="select*fromtbl_weightwhere wc>"+start+"andwc<="+end+"";
Thread.sleep(2000);
tableview1tv=newtableview1();
tv.table(sel_qry,"Cluster---"+(i+1) );
start=end;
end=start+end;
}
Runtime run1= Runtime.getRuntime();
double free1= run1.freeMemory();
double total1= run1.totalMemory();
double used1= total1- free1;
double total_exememrory=used1- used;

33. floatumemory= (float) total_exememrory/1024/10;
System.out.println("-UsedMemory--"+umemory);
double Endtime =System.nanoTime();
double ExeTime =(Endtime - starttime1) /60 / 60/10;
System.out.println("Total ExecutionTime "+ExeTime/10000);
Stringinsert_performence="insertintotbl_performence_fcmvalues( 'KMeansClustering ',
'ExecutionTime','"+Math.abs(ExeTime )/10000+"') ";
db.st.executeUpdate(insert_performence);
Stringinsert_performence1="insertintotbl_performence_fcmvalues( 'KMeansClustering
', 'Memory', '"+Math.abs(umemory)+"') ";
db.st2.executeUpdate(insert_performence1);
}catch(Exceptionexpp)
{
expp.printStackTrace();
}

34. }
}