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this should help some

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jenzur
2019-03-24 23:04:19 +01:00
parent c5c1a31a14
commit e07a9d7601
5 changed files with 377 additions and 288 deletions
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ArtificialAutism/src/main/java/FunctionLayer/StanfordParser/SentimentAnalyzerTest.java
+9 -2
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@@ -18,7 +18,10 @@ import edu.stanford.nlp.neural.rnn.RNNCoreAnnotations;
import edu.stanford.nlp.parser.shiftreduce.ShiftReduceParser;
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.process.CoreLabelTokenFactory;
import edu.stanford.nlp.process.DocumentPreprocessor;
import edu.stanford.nlp.process.PTBTokenizer;
import edu.stanford.nlp.process.TokenizerFactory;
import edu.stanford.nlp.sentiment.SentimentCoreAnnotations;
import edu.stanford.nlp.sequences.DocumentReaderAndWriter;
import edu.stanford.nlp.tagger.maxent.MaxentTagger;
@@ -94,10 +97,14 @@ public class SentimentAnalyzerTest implements Callable<SimilarityMatrix> {
List<List<TaggedWord>> taggedwordlist1 = new ArrayList();
List<List<TaggedWord>> taggedwordlist2 = new ArrayList();
DocumentPreprocessor tokenizer = new DocumentPreprocessor(new StringReader(str1));
TokenizerFactory<CoreLabel> ptbTokenizerFactory
= PTBTokenizer.factory(new CoreLabelTokenFactory(), "untokenizable=noneKeep");
tokenizer.setTokenizerFactory(ptbTokenizerFactory);
for (List<HasWord> sentence : tokenizer) {
taggedwordlist1.add(model.apply(tagger.tagSentence(sentence)).taggedYield());
}
tokenizer = new DocumentPreprocessor(new StringReader(str));
tokenizer.setTokenizerFactory(ptbTokenizerFactory);
for (List<HasWord> sentence : tokenizer) {
taggedwordlist2.add(model.apply(tagger.tagSentence(sentence)).taggedYield());
}
@@ -192,7 +199,7 @@ public class SentimentAnalyzerTest implements Callable<SimilarityMatrix> {
}
}
} catch (Exception ex) {
System.out.println("pipelineAnnotation stacktrace: " + ex.getLocalizedMessage()+ "\n");
System.out.println("pipelineAnnotation stacktrace: " + ex.getLocalizedMessage() + "\n");
}
sentenceConstituencyParseList.clear();
ConcurrentMap<Integer, SimpleMatrix> simpleSMXlist = new MapMaker().concurrencyLevel(2).makeMap();
@@ -422,7 +429,7 @@ public class SentimentAnalyzerTest implements Callable<SimilarityMatrix> {
score -= tokensCounter1 >= tokensCounter2 ? (tokensCounter1 - tokensCounter2) * 500 : (tokensCounter2 - tokensCounter1) * 500;
}
LevenshteinDistance leven = new LevenshteinDistance(str, str1);
int SentenceScoreDiff = leven.computeLevenshteinDistance();
double SentenceScoreDiff = leven.computeLevenshteinDistance();
SentenceScoreDiff *= 15;
score -= SentenceScoreDiff;
} catch (Exception ex) {