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POSimilarity Matrix from DocumentTermmatrix
 

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  1. POSimilarity Matrix from DocumentTermmatrix
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    <p>I need to create a similarity matrix from a document term matrix in order to perform maximum capturing clusturing on documents. Have only found a solution for distance matrix so far. Tryed the dist method but it gives me the wrong output. Is there a way to create similarity matrixes using R? I used the tm package for the following code but i am not constricted to it, if there is any other good package, let me know. The code so far:</p> <pre><code>install.packages("tm") install.packages("rJava") install.packages("Snowball") install.packages("RWeka") install.packages("RWekajars") install.packages("XML") install.packages("openNLP") install.packages("openNLPmodels.en") Sys.setenv(NOAWT=TRUE) library(XML) library(rJava) library(Snowball) library(RWeka) library(tm) library(openNLP) library(openNLPmodels.en) sample = c( "cc ee aa", "dd bb ee", "bb cc ee dd", "cc ee dd aa", "bb ee", "cc dd aa", "bb cc aa", "bb cc", "cc ee dd" ) print(sample) corpus &lt;- Corpus(VectorSource(sample)) inspect(corpus) corpus &lt;- tm_map(corpus, removeNumbers) corpus &lt;- tm_map(corpus, removePunctuation) corpus &lt;- tm_map(corpus, tolower) corpus &lt;- tm_map(corpus, removeWords, stopwords("english")) corpus &lt;- tm_map(corpus, stemDocument,language="english") corpus &lt;- tm_map(corpus, stripWhitespace) corpus &lt;- tm_map(corpus, tmTagPOS) inspect(corpus) dtm &lt;- DocumentTermMatrix(corpus) inspect(dtm) # need to create similarity matrix here dist(dtm, method = "manhattan", diag = FALSE, upper = FALSE) </code></pre> <p>The output for the given sample should look like this</p> <p><img src="https://i.stack.imgur.com/xwIYJ.jpg" alt="Similarity matrix"></p> <p>The similarity matrix is defined as:</p> <pre><code>if (i &lt; j) a[i][j] = sim[i][j] else a[i][j] = 0 </code></pre>
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    1. COyes, thank you, edited my post.
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    2. COyou use `upper = FALSE` and you want an upper matrix as result...andd when I use your code your dtm has 9 documents with zero length terms...so a distance matrix here will be NAN here. I am really curious how do you kno the desired output?
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    3. COwhen i inspect my dtm i have 9 documents including 9 terms... the expected output for the given sample is described in the paper about maximum capturing: http://140.134.131.64/wiki/images/8/82/2010-08-04_%28J-2010%29-_Text_Clustering_using_Frequent_Itemsets.pdf
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