Document Clustering in Matlab - matlab

Question

I am working on a code for document clustering in matlab. My document is :
'The first step in analyzing the requirements is to construct an object model.
It describes real world object classes and their relationships to each other.
Information for the object model comes from the problem statement, expert knowledge of the application domain, and general knowledge of the real world.
Britvic plc is one of the leading soft drinks manufacturers of soft drinks in the Beverages Sector functioning in Europe with its distribution branches in Great Britain, Ireland and France. '
As seen, the paragraphs contain different classes of data. The following is my main program:
global n;
n=1;
file1=fopen('doc1.txt','r');
%file 1 is now open
%read data from file 1
text=fileread('doc1.txt');
i=0;
%now text1 has the content of doc1 as a string.Next split the sentences
%into words.For that we are calling the split function
[C1,C2]=clustering(text)
And below comes the code for 'clustering':
function [C1,C2]=clustering(text)
global C1;
text1=strsplit(text,'.');
[rt1,ct1]=size(text1);
for i=1:(ct1-1)
var=text1{i};
vv=strsplit(var,' ');
text2=setdiff(vv,{'this','you','is','an','with','as','well','like','and','to','it','on','off','of','in','mine','your','yours','these','this','will','would','shall','should','or','a','about','all','also','am','are','but','of','for','by','my','did','do','her','his','the','him','she','he','they','that','when','we','us','not','them','if','in','just','may','not'},'stable');
[rt2,ct2]=size(text2);
for r=1:ct2
tmar=porterStemmer(text2{r});
mapr{i,r}=tmar;
end
end
[mr,mc]=size(mapr);
mapr
A=zeros(mr,mr);
for i=1:mr
for j=1:mc
for m=i+1:mr
for k=1:mc
if ~isempty(mapr{i,j})
%if(~(mapr{i,j}=='[]'))
%mapr(i,j)
if strcmp(mapr{i,j},mapr{m,k})
p=mapr{i,j};
str=sprintf('Sentences %d and %d match',i,m)
str;
str1=sprintf('And the word is : %s ',p)
str1;
A(i,m)=1;
A(m,i)=1;
end
end
end
end
end
end
sprintf('Adjacency matrix is:')
A
sprintf('The corresponding diagonnal matrix is:')
[ar,ac]=size(A);
for i=1:ar
B(i)=0;
for j=1:ac
B(i)=B(i)+A(i,j);
end
end
[br,bc]=size(B);
D=zeros(bc,bc);
for i=1:bc
D(i,i)=B(i);
end
D
sprintf('The similarity matrix is:')
C=D-A
[V,D]=eig(C,'nobalance')
F=inv(V);
V*D*F
%mvar =no of edges/total degree of vertices
no_of_edges=0;
for i=1:ar
for j=1:ac
if(i<=j)
no_of_edges=no_of_edges+A(i,j);
end
end
end
no_of_edges;
tdv=0;
for i=1:bc
tdv=tdv+B(i);
end
tdv;
mvar=no_of_edges/tdv
[dr,dc]=size(D);
temp=abs(D(1,1)-mvar);
x=D(1,1);
for i=2:dc
temp2=abs(D(i,i)-mvar);
if temp>temp2
temp=temp2;
x=D(i,i);
q=i
end
end
x
[vr,vc]=size(V);
for i=1:vr
V(i,q);
Track(i)=V(i,q);
end
sprintf('Eigen vectors corresponding to the closest value:')
Track
j=1;
m=1;
C1=' ';
C2=' ';
for i=1:vr
if(Track(i)<0)
C1=strcat(C1,text1{1,i},'.');
else
C2=strcat(C2,text1{1,i},'.');
end
end
I could generate the initial two clusters from the document. But then again, I want the clustering process to continue on the generated clusters producing more and more subclusters of each untill there is no change in the population generated. Can somebody help me implement a solution to this so that I can not only generate the clusters but also to keep track of them for further processing. Thanks in advance.