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Word Clustering

elouanesb90elouanesb90 Member Posts: 3 Contributor I
edited June 2019 in Help
I have a set of Document and I want to applay a clustering of the word not the document In other way I want use unseprvise clustering to extract Word similarity in the document based on word occoronce

Best Answer

  • Thomas_OttThomas_Ott RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,760   Unicorn
    Solution Accepted

    Try this example.


    <?xml version="1.0" encoding="UTF-8"?><process version="7.4.000">
    <operator activated="true" class="process" compatibility="7.4.000" expanded="true" name="Process">
    <parameter key="encoding" value="SYSTEM"/>
    <process expanded="true">
    <operator activated="true" class="social_media:search_twitter" compatibility="7.3.000" expanded="true" height="68" name="Search Twitter" width="90" x="45" y="34">
    <parameter key="connection" value="NewConnection"/>
    <parameter key="query" value="RapidMiner"/>
    <parameter key="language" value="en"/>
    <operator activated="true" class="select_attributes" compatibility="7.4.000" expanded="true" height="82" name="Select Attributes" width="90" x="179" y="34">
    <parameter key="attribute_filter_type" value="subset"/>
    <parameter key="attributes" value="Retweet-Count|Text"/>
    <operator activated="true" class="nominal_to_text" compatibility="7.4.000" expanded="true" height="82" name="Nominal to Text" width="90" x="313" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="Text"/>
    <operator activated="true" class="set_role" compatibility="7.4.000" expanded="true" height="82" name="Set Role" width="90" x="447" y="34">
    <parameter key="attribute_name" value="Retweet-Count"/>
    <parameter key="target_role" value="label"/>
    <list key="set_additional_roles"/>
    <operator activated="true" class="text:process_document_from_data" compatibility="7.4.001" expanded="true" height="82" name="Process Documents from Data" width="90" x="581" y="34">
    <parameter key="prune_method" value="percentual"/>
    <list key="specify_weights"/>
    <process expanded="true">
    <operator activated="true" class="text:tokenize" compatibility="7.4.001" expanded="true" height="68" name="Tokenize" width="90" x="45" y="34"/>
    <operator activated="true" class="text:filter_stopwords_english" compatibility="7.4.001" expanded="true" height="68" name="Filter Stopwords (English)" width="90" x="179" y="34"/>
    <operator activated="true" class="text:filter_by_length" compatibility="7.4.001" expanded="true" height="68" name="Filter Tokens (by Length)" width="90" x="313" y="34">
    <parameter key="min_chars" value="2"/>
    <operator activated="true" class="text:stem_porter" compatibility="7.4.001" expanded="true" height="68" name="Stem (Porter)" width="90" x="447" y="34"/>
    <operator activated="true" class="text:transform_cases" compatibility="7.4.001" expanded="true" height="68" name="Transform Cases" width="90" x="581" y="34"/>
    <connect 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="Stem (Porter)" to_port="document"/>
    <connect from_op="Stem (Porter)" from_port="document" to_op="Transform Cases" to_port="document"/>
    <connect from_op="Transform Cases" 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="k_means" compatibility="7.4.000" expanded="true" height="82" name="Clustering" width="90" x="715" y="34"/>
    <connect from_op="Search Twitter" from_port="output" to_op="Select Attributes" to_port="example set input"/>
    <connect from_op="Select Attributes" from_port="example set output" to_op="Nominal to Text" to_port="example set input"/>
    <connect from_op="Nominal to Text" from_port="example set output" to_op="Set Role" to_port="example set input"/>
    <connect from_op="Set Role" from_port="example set 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 1"/>
    <connect from_op="Clustering" from_port="clustered 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"/>


  • Thomas_OttThomas_Ott RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,760   Unicorn

    Did you search through the Community for a sample process or attempt one on your own?

  • elouanesb90elouanesb90 Member Posts: 3 Contributor I

    yes I do my search but it alowas abut document clustering not word or Term clustering.

    for my attempt I try to do the same thing in document clustering using the word output of Text processing operation as input of the K-means clustering operation but it still not good

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