'nominal correllation matrix' from example set

imke

Hello,

I have already done a text mining process and now I have the Example Set (Process Documents from Data) table. With this I want to calculate how often two words occur in the same text. At first I thought I could use Correlation Matrix Operator, but that does not work. So I tryed with Auto Model the Clustring, but for this I can only take two entrys of the example Set and I want to know it from all the words. So I thought maybe I could add the x-Means Operator in my process, but for x-Means my Data Set is a way to big and with k-Means I'm not getting the results I want. (No Correlation Matrix like with Auto Model anymore).

So  my question is: Is there a possibility to create a correlation Matrix with the ExampleSet?

Thank you

Imke

MartinLiebig

Hi @imke,

it feels to me like this is a case for FP-Growth or for n_grams? See attached example.

 

BR,

Martin

 

<?xml version="1.0" encoding="UTF-8"?><process version="9.0.002">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="9.0.002" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="text:create_document" compatibility="8.1.000" expanded="true" height="68" name="Create Document" width="90" x="112" y="85">
        <parameter key="text" value="one two three"/>
      </operator>
      <operator activated="true" class="text:create_document" compatibility="8.1.000" expanded="true" height="68" name="Create Document (2)" width="90" x="112" y="238">
        <parameter key="text" value="two three four"/>
      </operator>
      <operator activated="true" class="collect" compatibility="9.0.002" expanded="true" height="103" name="Collect" width="90" x="246" y="187"/>
      <operator activated="true" class="text:process_documents" compatibility="8.1.000" expanded="true" height="103" name="Process Documents" width="90" x="380" y="187">
        <parameter key="vector_creation" value="Binary Term Occurrences"/>
        <process expanded="true">
          <operator activated="true" class="text:tokenize" compatibility="8.1.000" expanded="true" height="68" name="Tokenize" width="90" x="380" y="187"/>
          <connect from_port="document" to_op="Tokenize" to_port="document"/>
          <connect from_op="Tokenize" from_port="document" to_port="document 1"/>
          <portSpacing port="source_document" spacing="0"/>
          <portSpacing port="sink_document 1" spacing="0"/>
          <portSpacing port="sink_document 2" spacing="0"/>
        </process>
        <description align="center" color="transparent" colored="false" width="126">Binary term occs</description>
      </operator>
      <operator activated="true" class="numerical_to_binominal" compatibility="9.0.002" expanded="true" height="82" name="Numerical to Binominal" width="90" x="581" y="187"/>
      <operator activated="true" class="concurrency:fp_growth" compatibility="9.0.002" expanded="true" height="82" name="FP-Growth" width="90" x="715" y="187">
        <enumeration key="must_contain_list"/>
      </operator>
      <connect from_op="Create Document" from_port="output" to_op="Collect" to_port="input 1"/>
      <connect from_op="Create Document (2)" from_port="output" to_op="Collect" to_port="input 2"/>
      <connect from_op="Collect" from_port="collection" to_op="Process Documents" to_port="documents 1"/>
      <connect from_op="Process Documents" from_port="example set" to_op="Numerical to Binominal" to_port="example set input"/>
      <connect from_op="Numerical to Binominal" from_port="example set output" to_op="FP-Growth" to_port="example set"/>
      <connect from_op="FP-Growth" from_port="frequent sets" to_port="result 1"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
    </process>
  </operator>
</process>

imke

Hello Martin,

that's quite good, but not the right solution for me I think. N-grams are only words which are following themselfs and I want to know, which words are in wich text together, but not directly after the other word. Do you know what I mean?

Greatings

Imke

imke

Hello Martin,

I need to correct myself. With the right settings FP-Growth is perfect for me!

Thanks a lot!

Imke