我使用 Stanford core NLP情感分析库。下面的代码返回了一个例子的类,但我怎样才能得到分数呢?例如 -0.3 表示负等
private int getScore(String line) {
boolean isrun = false;
StanfordCoreNLP pipeline = null;
if(!isrun){
Properties props = getProperties();
pipeline = new StanfordCoreNLP(props);
isrun = true;
}
Annotation annotation;
int sentiment = -1;
if (line != null && line.length() > 0) {
annotation = pipeline.process(line);
for (CoreMap sentence : annotation.get(CoreAnnotations.SentencesAnnotation.class)) {
Tree tree = sentence.get(SentimentCoreAnnotations.AnnotatedTree.class);
sentiment = RNNCoreAnnotations.getPredictedClass(tree);
}
}
return sentiment;
}
编辑
在线demo当鼠标位于图表的根部时,我们可以看到该示例为负 72%。如何获得这个数字?
最佳答案
0.下载斯坦福NLP核心库并导入外部库stanford-corenlp-3.5.2-models.jar、stanford-corenlp-3.5.2.jar、stanford-corenlp-3.5.2-sources.jar和ejml- 0.23.jar 到这个包中。
1.在Eclipse中构建此类NLP
import java.util.Properties;
import org.ejml.simple.SimpleMatrix;
import edu.stanford.nlp.ling.CoreAnnotations;
import edu.stanford.nlp.neural.rnn.RNNCoreAnnotations;
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.sentiment.SentimentCoreAnnotations;
import edu.stanford.nlp.sentiment.SentimentCoreAnnotations.SentimentAnnotatedTree;
import edu.stanford.nlp.trees.Tree;
import edu.stanford.nlp.util.CoreMap;
public class NLP {
static StanfordCoreNLP pipeline;
public static void init() {
Properties props = new Properties();
props.setProperty("annotators", "tokenize, ssplit, parse, sentiment");
pipeline = new StanfordCoreNLP(props);
}
public static int findSentiment(String tweet) {
int mainSentiment = 0;
if (tweet != null && tweet.length() > 0) {
int longest = 0;
Annotation annotation = pipeline.process(tweet);
for (CoreMap sentence : annotation
.get(CoreAnnotations.SentencesAnnotation.class)) {
Tree tree = sentence
.get(SentimentAnnotatedTree.class);
int sentiment = RNNCoreAnnotations.getPredictedClass(tree);
SimpleMatrix sentiment_new = RNNCoreAnnotations.getPredictions(tree);
String partText = sentence.toString();
if (partText.length() > longest) {
mainSentiment = sentiment;
longest = partText.length();
}
}
}
return mainSentiment;
}
}
2.建立一个新类来用NLP解析你的句子
import java.util.ArrayList;
public class What2Think {
public static void main(String[] args) {
ArrayList<String> tweets = new ArrayList<String>();
tweets.add("In this country, \"democracy\" means pro-government. #irony");
NLP.init();
for(String tweet : tweets) {
System.out.println(tweet + " : " + NLP.findSentiment(tweet));
}
}
}
运行它
关于java - 斯坦福情感分析评分java,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/28014779/