Lucene三（索引加权）

　　在建立索引的时候，为指定的Document对象加权会增加该文档的评分，使其在搜索结果中靠前。使用Document对象的setBoost方法可以为索引加权，代码如下：

先来测试一下不加权时索引的搜索结果，需要一个search方法：

public void search() {
try {
IndexReader reader = IndexReader.open(directory);
IndexSearcher searcher = new IndexSearcher(reader);
TermQuery query = new TermQuery(new Term("content","like"));
TopDocs tds = searcher.search(query, 10);
for(ScoreDoc sd:tds.scoreDocs) {
Document doc = searcher.doc(sd.doc);
System.out.println("("+sd.doc+")"+doc.get("name")+"["+doc.get("email")+"]-->"+doc.get("id"));
}
reader.close();
} catch (CorruptIndexException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}

单元测试：

@Test
public void testSearch(){
IndexUtil iu = new IndexUtil();
iu.search();
}

测试输出结果：

(4)mike[[e-mail]]-->5
(3)jetty[[e-mail]]-->4
(5)jake[[e-mail]]-->6
(0)zhangsan[[e-mail]]-->1
(1)lisi[[e-mail]]-->2
(2)john[[e-mail]]-->3

修改添加索引方法Index，为指定索引加权，这里修改前先使用了一个map来存储权值信息，红色部分为加权的代码：

public class IndexUtil {

private String[] ids = {"1","2","3","4","5","6"};
private String[] emails = {"[e-mail]","[e-mail]","[e-mail]","[e-mail]","[e-mail]","[e-mail]"};
private String[] contents = {
"welcome to visited the space,I like book",
"hello boy, I like pingpeng ball",
"my name is cc I like game",
"I like football",
"I like football and I like basketball too",
"I like movie and swim"
};
private Date[] dates = null;
private int[] attachs = {2,3,1,4,5,5};
private String[] names = {"zhangsan","lisi","john","jetty","mike","jake"};
//用于存放加权信息
private Map<String,Float> scores = new HashMap<String,Float>();
private Directory directory = null;

public IndexUtil() {
try {
scores.put("itat.org",2.0f);
scores.put("zttc.edu", 1.5f);
directory = FSDirectory.open(new File("F:\\stady\\JAVA\\other\\Lucene\\test\\index02"));
} catch (IOException e) {
e.printStackTrace();
}
}

/**
* 建立索引
*/
public void index(){
IndexWriter writer = null;
try {
writer = new IndexWriter(directory, new IndexWriterConfig(Version.LUCENE_35, new StandardAnalyzer(Version.LUCENE_35)));
//创建前先删除索引
writer.deleteAll();
Document doc = null;
for(int i = 0; i < ids.length; i++){
doc = new Document();
doc.add(new Field("id", ids[i], Field.Store.YES,Field.Index.NOT_ANALYZED_NO_NORMS));
doc.add(new Field("email",emails[i],Field.Store.YES,Field.Index.NOT_ANALYZED));
doc.add(new Field("content",contents[i],Field.Store.NO,Field.Index.ANALYZED));
doc.add(new Field("name",names[i],Field.Store.YES,Field.Index.NOT_ANALYZED_NO_NORMS));
String et = emails[i].substring(emails[i].lastIndexOf("@")+1);
//加权操作。默认为1.0f
if(scores.containsKey(et)) {
doc.setBoost(scores.get(et));
} else {
doc.setBoost(0.5f);
}
writer.addDocument(doc);
}
} catch (CorruptIndexException e) {
e.printStackTrace();
} catch (LockObtainFailedException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
} finally{
try {
if(writer != null) writer.close();
} catch (CorruptIndexException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
}
}

}

再次运行单元测试方法testSearch,运行结果为：

(5)jake[[e-mail]]-->6
(0)zhangsan[[e-mail]]-->1
(1)lisi[[e-mail]]-->2
(4)mike[[e-mail]]-->5
(3)jetty[[e-mail]]-->4
(2)john[[e-mail]]-->3

明显看到此时加权成功！