source: nutchez-0.1/tomcat/webapps/ROOT/cluster.jsp @ 253

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<%

// @author Dawid Weiss
//
// PERFORMANCE/USER INTERFACE NOTE:
//
// What I do here is merely a demonstration. In real life the clustering
// process should be done in a separate "processing" stream, most likely
// a separate HTML frame that the user's browser requests data to.
// We don't want the user to wait with plain snippets until the clusters
// are created.
//
// Also: clustering is resource consuming, so a cache of recent queries 
// would be in place. Besides, such cache would also be beneficial for the
// purpose of re-querying existing clusters (remember that the
// clustering extension may be a heuristic returning a DIFFERENT set of
// clusters for an identical input).
// See www.vivisimo.com for details of how this can be done using frames, or
// http://carrot.cs.put.poznan.pl for an example of a Javascript solution.

// cluster the hits
HitsCluster [] clusters = null;
if (clusterer != null) {
  final long clusteringStart = System.currentTimeMillis();
  try {
    clusters = clusterer.clusterHits( details, Summary.toStrings(summaries) );
    final long clusteringDuration = System.currentTimeMillis() - clusteringStart;
    bean.LOG.info("Clustering took: " + clusteringDuration + " milliseconds.");
  } catch (Exception e) {
    // failed to do clustering (see below)
  }
}

if (clusterer == null) {
  %>No clustering extension found.<%
} else {
  if (clusters == null) {
    %>Unable to do clustering.<%
  } else if (clusters.length == 0) {
    %>No clusters found.<%
  } else {
    // display top N clusters and top Q documents inside them.
    int N = 10;
    int Q = 3;
    int maxLabels = 2;
    
    int displayCounter = 0;
    N = Math.min(N, clusters.length );

    for (int clusterIndex = 0 ; clusterIndex < N ; clusterIndex++) {
      HitsCluster cluster = clusters[ clusterIndex ];
      String [] clusterLabels = cluster.getDescriptionLabels();
      
      // probably leave it on for now
      //if (cluster.isJunkCluster()) continue;

      // output cluster label.
      %><div style="margin: 0px; padding: 0px; font-weight: bold;"><%
      for (int k=0;k<maxLabels && k<clusterLabels.length;k++) {
        if (k>0) out.print(", ");
        out.print( Entities.encode(clusterLabels[k]) );
      }
      %></div><%
       
      // now output sample documents from the inside
      HitDetails[] documents = cluster.getHits();
      if (documents.length > 0) {
        %><ul style="font-size: 90%; margin-top: .5em;"><%
        for (int k = 0; k < Q && k < documents.length; k++) {
          HitDetails detail = documents[ k ];
          String title = detail.getValue("title");
          String url = detail.getValue("url");
          if (title == null || title.equals("")) title = url;
          if (title.length() > 35) title = title.substring(0,35) + "...";
          %>
            <li><a href="<%=url%>"><%= Entities.encode(title) %></a></li>
          <%
        }
        %></ul><%
      }
       
      // ignore subclusters for now, ALTHOUGH HIERARCHICAL CLUSTERING
      // METHODS DO EXIST AND ARE VERY USEFUL
      // HitsCluster [] subclusters = cluster.getSubclusters();
    }
  }
}

%>