model.xml

<project name='project' pubsub='auto' threads='1' use-tagged-token='true'> 
    <description> 
	This project is a basic demonstration of using the Term Frequency - Inverse
	Document Frequency (TFIDF) algorithm. TFIDF is a weight that shows how important 
	a word is to a document in a document collection. TFIDF increases proportionally
	to the frequency with which each word appears in a document, but is offset by the
	frequency with which the word appears in the document collection. TFIDF can be used
	as a weighing factor in text mining or general information searches. 

	This project contains a single continuous query consisting of the following: 
	1.	A source window that receives scored data from a score window to be analyzed 
	2.	A calculate window that runs the TFIDF algorithm
    </description>
      <contqueries>
        <contquery name='contquery' trace='w_source w_evaluating'>
          <windows>
            <window-source name='w_source' insert-only='true' index='pi_EMPTY'> 
            <description> 
		This source window receives data events from the included example input via
		a file socket connector. The input stream is placed into three fields for
		each observation: two key fields named docID and tokenID; and a string named
		token.
            </description>
              <schema>
                <fields>
                  <field name='docId'  type='int64' key='true'/>
                  <field name='tokenId' type='int64' key='true'/>
                  <field name='token'  type='string' key='false'/>
                </fields>
              </schema>
              <connectors>
                <connector class='fs' name='publisher'>
                  <properties>
                    <property name='type'>pub</property>
                    <property name='fstype'>csv</property>
                    <property name='fsname'>input.csv</property>
                    <property name='transactional'>true</property>
                    <property name='blocksize'>1</property>
                  </properties>
                </connector>
              </connectors>
            </window-source>
            <window-calculate algorithm="TFIDF" name="w_calculate" index='pi_EMPTY'> 
            <description> 
		This calculate window receives data events from the source window, and publishes
		calculated transforms according to the TFIDF algorithm properties that are specified. 
		For this example, the following input-map and output-map define this window: 

		docId:		Specifies the input variable for the unique doc ID (key).
		tokenId:	Specifies the input variable for the token ID (key). 
		token:		Specifies the input token string. 

		docIdOut:	Specifies the output varable for the unique doc ID (key).
		tokenIdOut:	Specifies the output variable for the unique ID of the token. It is a 
				key when the word vectors are output. It is not a key when the document
				vectors are output. 
		tokenOut:	Specifies the output variable for the token. 
		tfOut:		Specifies the output variable for the term frequency (TF). 
		idfOut:		Specifies the output variable for the inverse document frequency (IDF). 
		tfidfOut:	Specifies the output variable for the TFIDF 

		The resulting output is written to the file result.out via a file socket connector.
	    </description>
              <schema>
                <fields>
                  <field key="true" name="docId"  type="int64" />
                  <field key="true" name="tokenId"    type="int64" />
                  <field key="false" name="token" type="string" />
                  <field key="false" name="tf"    type="double"/>
                  <field key="false" name="idf"   type="double"/>
                  <field key="false" name="tfidf" type="double"/>
                </fields>
              </schema>
              <input-map>
                <properties>
                  <property name="docId">docId</property>
                  <property name="tokenId">tokenId</property>
		  <property name="token">token</property>
                </properties>
              </input-map>
              <output-map>
                <properties>
                  <property name="docIdOut">docId</property>
                  <property name="tokenIdOut">tokenId</property>
                  <property name="tokenOut">token</property>
                  <property name="tfOut">tf</property>
                  <property name="idfOut">idf</property>
                  <property name="tfidfOut">tfidf</property>
                </properties>
              </output-map>
            
               <connectors>
		<connector name="csv" class="fs">
		  <properties>
		    <property name='type'>sub</property>
		    <property name='fstype'>csv</property>
		    <property name='fsname'>result.out</property>
		    <property name='snapshot'>true</property> 
                    <property name='header'>true</property>
		</properties>
	      </connector>
	    </connectors>
	   </window-calculate>
          </windows>
          <edges>
            <edge source='w_source' target='w_calculate' role='data'/>
          </edges>
        </contquery>
      </contqueries>
    </project>