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Java example source code file (SWN3.java)

This example Java source code file (SWN3.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

analysisengine, bufferedreader, casexception, classpathresource, double, exception, hashmap, hashset, iterator, serializable, set, string, swn3, util, vector

The SWN3.java Java example source code

/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://www.apache.org/licenses/LICENSE-2.0
 *  *
 *  *    Unless required by applicable law or agreed to in writing, software
 *  *    distributed under the License is distributed on an "AS IS" BASIS,
 *  *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  *    See the License for the specific language governing permissions and
 *  *    limitations under the License.
 *
 */

package org.deeplearning4j.text.corpora.sentiwordnet;

import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.io.Serializable;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Set;
import java.util.Vector;

import org.apache.uima.analysis_engine.AnalysisEngine;
import org.apache.uima.cas.CAS;
import org.apache.uima.cas.CASException;
import org.apache.uima.fit.util.JCasUtil;
import org.canova.api.util.ClassPathResource;
import org.cleartk.token.type.Sentence;
import org.cleartk.token.type.Token;
import org.deeplearning4j.text.tokenization.tokenizerfactory.UimaTokenizerFactory;

import com.google.common.collect.Sets;
/**
 * Based on SentiWordnet
 * @author Adam Gibson
 *
 */
public class SWN3 implements Serializable {
	/**
	 * 
	 */
	private static final long serialVersionUID = -2614454572930777658L;
	private HashMap<String, Double> _dict;
	private Set<String> negationWords = Sets.newHashSet("could","would","should","not","isn't","aren't","wasn't","weren't","haven't","doesn't","didn't","don't");
	private AnalysisEngine analysisEngine;
	
	public SWN3() throws Exception {
		this(UimaTokenizerFactory.defaultAnalysisEngine());
	}

	public SWN3(AnalysisEngine analysisEngine) {
		this("/sentiment/sentiwordnet.txt");
		this.analysisEngine = analysisEngine;
	}
	
	public SWN3(String sentiWordNetPath) {

		_dict = new HashMap<String, Double>();
		HashMap<String, Vector _temp = new HashMap>();

		ClassPathResource resource = new ClassPathResource(sentiWordNetPath);

		try{
			BufferedReader csv =  new BufferedReader(new InputStreamReader(resource.getInputStream()));
			String line = "";           
			while((line = csv.readLine()) != null) {
				if(line.isEmpty())
					continue;
				String[] data = line.split("\t");

				if(data[2].isEmpty() || data[3].isEmpty())
					continue;
				Double score = Double.parseDouble(data[2])-Double.parseDouble(data[3]);
				String[] words = data[4].split(" ");
				for(String w : words) {
					if(w.isEmpty())
						continue;

					String[] w_n = w.split("#");
					w_n[0] += "#"+data[0];
					int index = Integer.parseInt(w_n[1])-1;
					if(_temp.containsKey(w_n[0])) {
						Vector<Double> v = _temp.get(w_n[0]);
						if(index>v.size())
							for(int i = v.size();i<index; i++)
								v.add(0.0);
						v.add(index, score);
						_temp.put(w_n[0], v);
					}
					else {
						Vector<Double> v = new Vector();
						for(int i = 0;i<index; i++)
							v.add(0.0);
						v.add(index, score);
						_temp.put(w_n[0], v);
					}
				}
			}
			
			
			Set<String> temp = _temp.keySet();
			for (Iterator<String> iterator = temp.iterator(); iterator.hasNext(); ) {
				String word = iterator.next();
				Vector<Double> v = _temp.get(word);
				double score = 0.0;
				double sum = 0.0;
				for(int i = 0; i < v.size(); i++)
					score += ((double)1/(double)(i+1))*v.get(i);
				for(int i = 1; i<=v.size(); i++)
					sum += (double)1/(double)i;
				score /= sum;
				_dict.put(word, score);
			}
		}
		catch(Exception e) {
			throw new RuntimeException(e);
		}        
	}

	
	/**
	 * Classifies the given text
	 * @param text the text to classify
	 * @return the classification for the text
	 * @throws Exception
	 */
	public String classify(String text) throws Exception {
		return this.classForScore(score(text));
	}
	/**
	 * Scores the text
	 * @param words the text to score
	 * @return the score (polarity) for the text
	 * @throws Exception
	 */
	public double score(String words) throws Exception {
	 	CAS cas = analysisEngine.newCAS();
	 	cas.setDocumentText(words);
	 	analysisEngine.process(cas);
	 	return score(cas);
	}
	

	public String classForScore(Double score) {
		String sent = "neutral"; 
		if(score>=0.75)
			sent = "strong_positive";
		else if(score > 0.25 && score<=0.5)
			sent = "positive";
		else if(score > 0 && score>=0.25)
			sent = "weak_positive";
		else if(score < 0 && score>=-0.25)
			sent = "weak_negative";
		else if(score < -0.25 && score>=-0.5)
			sent = "negative";
		else if(score<=-0.75)
			sent = "strong_negative";
		return sent;
	}


	public String classify(CAS cas) throws CASException {
		return classForScore(score(cas));
	}



	public double scoreTokens(List<Token> tokens) {
		double totalScore = 0.0;
		Set<String> negativeWords = new HashSet();
		double scoreForSentence = 0.0;
		for(Token token : tokens) {
			scoreForSentence += extract(token.getCoveredText().toLowerCase());
			if(negationWords.contains(token.getCoveredText())) {
				negativeWords.add(token.getCoveredText());
			}
		}
		//flip for context
		if(!negativeWords.isEmpty()) {
			scoreForSentence *= -1.0;
		}

		totalScore +=scoreForSentence;
		return totalScore;
	}



	public double score(CAS cas) throws CASException {
		double totalScore = 0.0;
		for(Sentence sentence : JCasUtil.select(cas.getJCas(),Sentence.class)) {
			totalScore += scoreTokens(JCasUtil.selectCovered(Token.class,sentence));
		}

		return totalScore;
	}


	public String classify(Sentence sentence) {
		double totalScore = 0.0;
		for(Token token : JCasUtil.selectCovered(Token.class,sentence)) {
			totalScore += extract(token.getCoveredText().toLowerCase());
		}
		return classForScore(totalScore);
	}
	
	
	public double score(Sentence sentence) {
		double totalScore = 0.0;
		for(Token token : JCasUtil.selectCovered(Token.class, sentence)) {
			totalScore += extract(token.getCoveredText().toLowerCase());
		}
		return totalScore;
	}


	public Double extract(String word) {
		double total = 0.0;
		if(_dict.get(word + "#n") != null)
			total = _dict.get(word + "#n") + total;
		if(_dict.get(word + "#a") != null)
			total = _dict.get(word + "#a") + total;
		if(_dict.get(word + "#r") != null)
			total = _dict.get(word + "#r") + total;
		if(_dict.get(word + "#v") != null)
			total = _dict.get(word + "#v") + total;
		return total;
	}
	
	
	public static void main(String[] args) {
		SWN3 swn = new SWN3("/sentiment/sentiwordnet.txt");
		System.out.println(swn.classForScore(swn.extract("sad")));

	}
}

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