一、首先要引入mawen依赖包:

 <dependency>
<groupId>com.hankcs</groupId>
<artifactId>hanlp</artifactId>
<version>portable-1.7.2</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid</artifactId>
<version>1.1.10</version>
</dependency>
<dependency>
<groupId>org.jsoup</groupId>
<artifactId>jsoup</artifactId>
<version>1.7.3</version>
</dependency>

二、提取语句中的关键字

java.util.List<String> keyword =  HanLP.extractKeyword(model.getExamineeAnswer(), model.getKeywordList().size());//extractKeyword方法第二个参数为获取关键字个数
,第一个参数为你要提取关键字的语句

三、计算两个语句的相似度

 double result=getSimilarity(model.getStandardAnswer(),model.getExamineeAnswer());

计算相似度使用的方法

     /*     * 获得两个句子的相似度
* @param sentence1
* @param sentence2
* @return
*/
public static double getSimilarity(String sentence1, String sentence2) {
List<String> sent1Words = getSplitWords(sentence1);
System.out.println(sent1Words);
List<String> sent2Words = getSplitWords(sentence2);
System.out.println(sent2Words);
List<String> allWords = mergeList(sent1Words, sent2Words); int[] statistic1 = statistic(allWords, sent1Words);
int[] statistic2 = statistic(allWords, sent2Words); double dividend = 0;
double divisor1 = 0;
double divisor2 = 0;
for (int i = 0; i < statistic1.length; i++) {
dividend += statistic1[i] * statistic2[i];
divisor1 += Math.pow(statistic1[i], 2);
divisor2 += Math.pow(statistic2[i], 2);
} return dividend / (Math.sqrt(divisor1) * Math.sqrt(divisor2));
} private static int[] statistic(List<String> allWords, List<String> sentWords) {
int[] result = new int[allWords.size()];
for (int i = 0; i < allWords.size(); i++) {
result[i] = Collections.frequency(sentWords, allWords.get(i));
}
return result;
} private static List<String> mergeList(List<String> list1, List<String> list2) {
List<String> result = new ArrayList<>();
result.addAll(list1);
result.addAll(list2);
return result.stream().distinct().collect(Collectors.toList());
} private static List<String> getSplitWords(String sentence) {
// 去除掉html标签
sentence = Jsoup.parse(sentence.replace("&nbsp;","")).body().text();
// 标点符号会被单独分为一个Term,去除之
return HanLP.segment(sentence).stream().map(a -> a.word).
filter(s -> !"`~!@#$^&*()=|{}':;',\\[\\].<>/?~!@#¥……&*()——|{}【】‘;:”“'。,、? ".contains(s)).collect(Collectors.toList());
}

四、提取语句的摘要

List<String> sentenceList = HanLP.extractSummary(str, 3);//摘要

五、hanlp分词

List<Term> termList = NLPTokenizer.segment(str);

六、提取句子中的词

List<String> sentenceList= HanLP.extractPhrase(str, 3);//词
04-17 03:36