@@ -87,8 +87,8 @@ public class Pipeline {
8787 // placeholder for the topic posfix
8888 private static String TOPIC_NAME = null ;
8989 // placeholder for the used dataset
90- private final static String DATASET = "del " ;
91- private final static String SUBDIR = "/ipm3" ;
90+ private final static String DATASET = "twitter " ;
91+ private final static String SUBDIR = "" ; //" /ipm3";
9292
9393 public static void main (String [] args ) {
9494 System .out .println ("TagRecommender:\n " + "" +
@@ -113,14 +113,14 @@ public static void main(String[] args) {
113113 //TagReuseProbAnalyzer.analyzeSample(path, TRAIN_SIZE, TEST_SIZE, false);
114114
115115 //evaluate(dir, path, "pitf", TOPIC_NAME, true, true, null);
116- //try { getStatistics("bib_core/vedran/bib_bibtex_2_perc_1 ", false); } catch (Exception e) { e.printStackTrace(); }
116+ //try { getStatistics("twitter_core/seedUserTweets ", false); } catch (Exception e) { e.printStackTrace(); }
117117
118118 //JSONProcessor.writeJSONOutput("bib_core/vedran/bib_bibtex_2_perc_1");
119119
120120 //evaluateAllTagRecommenderApproaches(dir, path);
121121 //startAllTagRecommenderApproaches(dir, path, true);
122122 //getTrainTestStatistics(path);
123- //BookmarkSplitter.splitSample(DATASET + "_core/twitter ", DATASET + "_core/" + DATASET + "_sample ", 1, 0, true);
123+ //BookmarkSplitter.splitSample("twitter_core/seedUserTweets ", "twitter_core/twitter_sample ", 1, 0, true);
124124 //BookmarkSplitter.drawUserPercentageSample("bib_core/vedran/bib_bibtex", 5);
125125 //createLdaSamples("ml_core/core1/ml_sample", 1, 1000, true, true);
126126
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