Tailoring Text Mining Clusters

Hello. I am trying to classify electronic notebook items into one of three defined categories (clusters). My process does run and I get a count of notebooks into each of 3 clusters. Is there a way to tailor the creation of the clusters since I know generally the identity of what I want each of the 3 clusters to be but not the actual words which will identify the cluster? I'm thinking of something like PCA where I can select the words which would define a cluster. Any ideas would be appreciated.
Here is my XML:<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.2.003">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="5.2.003" expanded="true" name="Process">
    <process expanded="true" height="386" width="415">
      <operator activated="true" class="read_excel" compatibility="5.2.003" expanded="true" height="60" name="Read Excel" width="90" x="45" y="30">
        <parameter key="excel_file" value="E:\R-2.14.0\bin\i386\ELN.xls"/>
        <parameter key="imported_cell_range" value="A1:C301"/>
        <list key="annotations">
          <parameter key="0" value="Name"/>
        </list>
        <list key="data_set_meta_data_information">
          <parameter key="0" value="ELN.true.nominal.id"/>
          <parameter key="1" value="Title.true.text.attribute"/>
          <parameter key="2" value="Text.true.text.attribute"/>
        </list>
        <parameter key="read_not_matching_values_as_missings" value="false"/>
      </operator>
      <operator activated="true" class="text:process_document_from_data" compatibility="5.2.001" expanded="true" height="76" name="Process Documents from Data" width="90" x="112" y="120">
        <parameter key="keep_text" value="true"/>
        <parameter key="prune_below_absolute" value="1"/>
        <parameter key="prune_above_absolute" value="3"/>
        <list key="specify_weights"/>
        <process expanded="true" height="426" width="501">
          <operator activated="true" class="text:transform_cases" compatibility="5.2.001" expanded="true" height="60" name="Transform Cases" width="90" x="45" y="30"/>
          <operator activated="true" class="text:stem_snowball" compatibility="5.2.001" expanded="true" height="60" name="Stem (Snowball)" width="90" x="179" y="30"/>
          <operator activated="true" class="text:tokenize" compatibility="5.2.001" expanded="true" height="60" name="Tokenize" width="90" x="313" y="30"/>
          <operator activated="true" class="text:filter_stopwords_english" compatibility="5.2.001" expanded="true" height="60" name="Filter Stopwords (English)" width="90" x="45" y="165"/>
          <operator activated="true" class="text:filter_by_length" compatibility="5.2.001" expanded="true" height="60" name="Filter Tokens (by Length)" width="90" x="179" y="210">
            <parameter key="min_chars" value="2"/>
          </operator>
          <operator activated="true" class="text:generate_n_grams_terms" compatibility="5.2.001" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="313" y="255"/>
          <connect from_port="document" to_op="Transform Cases" to_port="document"/>
          <connect from_op="Transform Cases" from_port="document" to_op="Stem (Snowball)" to_port="document"/>
          <connect from_op="Stem (Snowball)" from_port="document" to_op="Tokenize" to_port="document"/>
          <connect from_op="Tokenize" from_port="document" to_op="Filter Stopwords (English)" to_port="document"/>
          <connect from_op="Filter Stopwords (English)" from_port="document" to_op="Filter Tokens (by Length)" to_port="document"/>
          <connect from_op="Filter Tokens (by Length)" from_port="document" to_op="Generate n-Grams (Terms)" to_port="document"/>
          <connect from_op="Generate n-Grams (Terms)" 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>
      </operator>
      <operator activated="true" class="k_means" compatibility="5.2.003" expanded="true" height="76" name="Clustering" width="90" x="45" y="300">
        <parameter key="add_as_label" value="true"/>
        <parameter key="k" value="3"/>
      </operator>
      <operator activated="true" class="select_attributes" compatibility="5.2.003" expanded="true" height="76" name="Select Attributes" width="90" x="179" y="300"/>
      <operator activated="true" class="write_csv" compatibility="5.2.003" expanded="true" height="76" name="Write CSV" width="90" x="313" y="300"/>
      <connect from_op="Read Excel" from_port="output" to_op="Process Documents from Data" to_port="example set"/>
      <connect from_op="Process Documents from Data" from_port="example set" to_op="Clustering" to_port="example set"/>
      <connect from_op="Clustering" from_port="cluster model" to_port="result 2"/>
      <connect from_op="Clustering" from_port="clustered set" to_op="Select Attributes" to_port="example set input"/>
      <connect from_op="Select Attributes" from_port="example set output" to_op="Write CSV" to_port="input"/>
      <connect from_op="Write CSV" from_port="file" 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"/>
      <portSpacing port="sink_result 3" spacing="0"/>
    </process>
  </operator>
</process>