HanLP分词器HanLPTokenizer怎么实现，针对这个问题，这篇文章详细介绍了相对应的分析和解答，希望可以帮助更多想解决这个问题的小伙伴找到更简单易行的方法。
anlp在功能上的扩展主要体现在以下几个方面:
•关键词提取
•自动摘要
•短语提取
•拼音转换
•简繁转换
•文本推荐
下面是 hanLP分词器的代码
注：使用maven依赖
<dependency>
<groupId>com.hankcs</groupId>
<artifactId>hanlp</artifactId>
<version>portable-1.3.4</version>
</dependency>
使用了java8进行处理
import java.util.ArrayList;
import java.util.List;
import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils;
import com.hankcs.hanlp.seg.Segment;
import com.hankcs.hanlp.seg.Dijkstra.DijkstraSegment;
import com.hankcs.hanlp.seg.NShort.NShortSegment;
import com.hankcs.hanlp.tokenizer.IndexTokenizer;
import com.hankcs.hanlp.tokenizer.NLPTokenizer;
import com.hankcs.hanlp.tokenizer.SpeedTokenizer;
import com.hankcs.hanlp.tokenizer.StandardTokenizer;
public class HanLPTokenizer {
private static final Segment N_SHORT_SEGMENT = new NShortSegment().enableCustomDictionary(false)
.enablePlaceRecognize(true).enableOrganizationRecognize(true);
private static final Segment DIJKSTRA_SEGMENT = new DijkstraSegment().enableCustomDictionary(false)
.enablePlaceRecognize(true).enableOrganizationRecognize(true);
public static List<String> standard(String text) {
List<String> list = new ArrayList<String>();
StandardTokenizer.segment(text).forEach(term -> {
if (StringUtils.isNotBlank(term.word)) {
list.add(term.word);
}
});
return list.stream().distinct().collect(Collectors.toList());
}
public static List<String> nlp(String text) {
List<String> list = new ArrayList<String>();
NLPTokenizer.segment(text).forEach(term -> {
if (StringUtils.isNotBlank(term.word)) {
list.add(term.word);
}
});
return list.stream().distinct().collect(Collectors.toList());
}
public static List<String> index(String text) {
List<String> list = new ArrayList<String>();
IndexTokenizer.segment(text).forEach(term -> {
if (StringUtils.isNotBlank(term.word)) {
list.add(term.word);
}
});
return list.stream().distinct().collect(Collectors.toList());
}
public static List<String> speed(String text) {
List<String> list = new ArrayList<String>();
SpeedTokenizer.segment(text).forEach(term -> {
if (StringUtils.isNotBlank(term.word)) {
list.add(term.word);
}
});
return list;
}
public static List<String> nShort(String text) {
List<String> list = new ArrayList<String>();
N_SHORT_SEGMENT.seg(text).forEach(term -> {
if (StringUtils.isNotBlank(term.word)) {
list.add(term.word);
}
});
return list.stream().distinct().collect(Collectors.toList());
}
public static List<String> shortest(String text) {
List<String> list = new ArrayList<String>();
DIJKSTRA_SEGMENT.seg(text).forEach(term -> {
if (StringUtils.isNotBlank(term.word)) {
list.add(term.word);
}
});
return list.stream().distinct().collect(Collectors.toList());
}
public static void main(String[] args) {
String text = "测试勿动12";
System.out.println("标准分词:" + standard(text));
System.out.println("NLP分词:" + nlp(text));
System.out.println("索引分词:" + index(text));
System.out.println("N-最短路径分词:" + nShort(text));
System.out.println("最短路径分词分词:" + shortest(text));
System.out.println("极速词典分词:" + speed(text));
}
}
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