1 | /**
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2 | * @(#)ClusterObj.java 12/12/99
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3 | * @author Peter Au
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4 | * All rights reserved.
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5 | */
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6 |
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7 | package vishnu.testvis.object;
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8 | import vishnu.datablock.*;
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9 | import java.util.Vector;
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10 |
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11 | public class ClusterObj
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12 | {
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13 | DocObj[] _docs; //-- list of DocObj ref
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14 | String _label; //-- (top 3-5? related words)
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15 | Point2D [] _sammon; //-- 2D mapping for the centroids
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16 | DataManager _data;
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17 | public ClusterObj(DocObj[] d, String t, Point2D [] sammon, DataManager dm)
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18 | {
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19 | _docs=d; _label=t;
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20 | _sammon = sammon;
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21 | _data = dm;
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22 | }
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23 | /**
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24 | * @return the number of documents in the cluster
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25 | */
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26 | public int getDocsSize(){return _docs.length;}
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27 |
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28 | public String getLabel(){return _label;}
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29 |
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30 | public String getLabel1(){return getDocsSize() + " documents found";}
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31 | public String getLabel2(){return getLabel();}
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32 |
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33 |
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34 | public String getInfo(){
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35 | return getDocsSize() + " documents found\n" + getLabel();
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36 | }
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37 |
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38 |
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39 | /**
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40 | * This returns a list of list of documents. The inner list of documents represents
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41 | * which documents have the corresponding related word
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42 | * pre: _docs can't be null
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43 | * @return a vector (same length as the related words) of
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44 | * vectors (arbitrary length)
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45 | *
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46 | */
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47 | public Vector getHitDocFreq()
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48 | {
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49 | int s = _data.getWordCount();
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50 | Vector rwVec = new Vector(s);
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51 | for(int i=0;i<s;i++)
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52 | {
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53 | rwVec.addElement(new Vector(0));
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54 | for(int j=0;j<_docs.length;j++)
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55 | {
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56 | if ( _docs[j].getWeights(i) > 0 )
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57 | ((Vector) rwVec.elementAt(i)).addElement(_docs[j]);
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58 | }
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59 | }
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60 | return rwVec;
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61 | }
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62 |
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63 |
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64 | public String formatDocs()
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65 | {
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66 | int l = getDocsSize();
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67 | String s = "<html><font face=Arial size=-1> "+ l +" documents found\n";
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68 | for(int i=0;i<l;i++)
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69 | {
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70 | s += _docs[i].format4Fields();
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71 | }
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72 | s += "</font></html>\n";
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73 | return s;
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74 | }
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75 |
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76 |
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77 | }
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