Remove Unwanted Words from List

ronmacronmac Member Posts: 11 Contributor II
edited June 2019 in Help
I would like to remove unwanted words from this project I am working on. I figured out I can use the Remove Documents Operator to get rid of "http" from my results. I have more words I would like to filter out. For example, "chart", "twitter", "trade", "message" etc. Can someone explain how I can expand the list of words to filter out. I would like to have the flexibility to make changes to the list as needed based on the search results. Also is the Stem Operator required for what I am doing here?

Ron McEwan
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.0">
  <operator activated="true" class="process" compatibility="5.0.11" expanded="true" name="Process">
    <process expanded="true" height="251" width="413">
      <operator activated="true" class="web:read_rss" compatibility="5.0.4" expanded="true" height="60" name="Read RSS Feed" width="90" x="45" y="30">
        <parameter key="url" value=""/>
      <operator activated="true" class="text:process_document_from_data" compatibility="5.0.7" expanded="true" height="76" name="Process Documents from Data" width="90" x="45" y="165">
        <parameter key="add_meta_information" value="false"/>
        <parameter key="keep_text" value="true"/>
        <parameter key="prune_method" value="absolute"/>
        <parameter key="prune_below_absolute" value="2"/>
        <parameter key="prune_above_absolute" value="999"/>
        <list key="specify_weights"/>
        <process expanded="true" height="408" width="570">
          <operator activated="true" class="text:remove_document_parts" compatibility="5.0.7" expanded="true" height="60" name="Remove Document Parts" width="90" x="45" y="30">
            <parameter key="deletion_regex" value="http"/>
          <operator activated="true" class="text:tokenize" compatibility="5.0.7" expanded="true" height="60" name="Tokenize" width="90" x="45" y="165"/>
          <operator activated="true" class="text:transform_cases" compatibility="5.0.7" expanded="true" height="60" name="Transform Cases" width="90" x="179" y="165"/>
          <operator activated="true" class="text:filter_by_length" compatibility="5.0.7" expanded="true" height="60" name="Filter Tokens (by Length)" width="90" x="313" y="165">
            <parameter key="max_chars" value="10"/>
          <operator activated="true" class="text:stem_snowball" compatibility="5.0.7" expanded="true" height="60" name="Stem (Snowball)" width="90" x="45" y="300"/>
          <operator activated="true" class="text:filter_stopwords_english" compatibility="5.0.7" expanded="true" height="60" name="Filter Stopwords (English)" width="90" x="179" y="300"/>
          <operator activated="true" class="text:generate_n_grams_terms" compatibility="5.0.7" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="313" y="300">
            <parameter key="max_length" value="3"/>
          <connect from_port="document" to_op="Remove Document Parts" to_port="document"/>
          <connect from_op="Remove Document Parts" from_port="document" to_op="Tokenize" to_port="document"/>
          <connect from_op="Tokenize" from_port="document" to_op="Transform Cases" to_port="document"/>
          <connect from_op="Transform Cases" from_port="document" to_op="Filter Tokens (by Length)" to_port="document"/>
          <connect from_op="Filter Tokens (by Length)" from_port="document" to_op="Stem (Snowball)" to_port="document"/>
          <connect from_op="Stem (Snowball)" from_port="document" to_op="Filter Stopwords (English)" to_port="document"/>
          <connect from_op="Filter Stopwords (English)" 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"/>
      <operator activated="true" class="mututal_information_matrix" compatibility="5.0.11" expanded="true" height="76" name="Mututal Information Matrix" width="90" x="277" y="219"/>
      <operator activated="true" class="text:wordlist_to_data" compatibility="5.0.7" expanded="true" height="76" name="WordList to Data" width="90" x="246" y="30"/>
      <connect from_op="Read RSS Feed" 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="Mututal Information Matrix" to_port="example set"/>
      <connect from_op="Process Documents from Data" from_port="word list" to_op="WordList to Data" to_port="word list"/>
      <connect from_op="Mututal Information Matrix" from_port="example set" to_port="result 3"/>
      <connect from_op="Mututal Information Matrix" from_port="matrix" to_port="result 4"/>
      <connect from_op="WordList to Data" from_port="word list" to_port="result 1"/>
      <connect from_op="WordList to Data" from_port="example set" to_port="result 2"/>
      <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"/>
      <portSpacing port="sink_result 4" spacing="0"/>
      <portSpacing port="sink_result 5" spacing="0"/>


  • ReneRene Member Posts: 24 Maven
    i never tried and i'm no RM-connaisseur. but i think you could e.g. use regular expressions to get rid of a short list of words: "http|chart|twitter". or create your own list of stop words and refer to it with a stopword-filter operator when you are working on tokens. "stemming" refers to reducing words to its roots - 'solicited', 'solicitation', 'unsolicited' etc. may e.g. all result in 'solicit' by using a stemming-algorithm.
  • B_B_ Member Posts: 70 Guru
    In text processing, filter stopwords (dictionary) uses a file for "personal stopwords."   
  • ronmacronmac Member Posts: 11 Contributor II
    Thanks for the help. The personal dictionary was exactly what I ineeded. Now I can modify this list as necessary. I also removed the Stem Operator. I had misunderstood it's application. 
  • gunjanamitgunjanamit Member Posts: 28 Contributor II
    How we can modify the dictionary?
  • rajbanokhanrajbanokhan Member Posts: 29 Maven


    there are so many words from 675 pages

    how to reduce words from list and i wanted only 30 to 40 important words

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