java使用Lucene使多值字段评分了解字段值计数
我试图将（多单词）标签列表与每个文档关联起来。 因此，对于每个文档，我都会添加多个StringField条目，并将“tag”作为fieldName
搜索时，我希望分数与我成功匹配的标签比例成正比，例如：
- 0.5如果我匹配一半的标签
- 1.0，如果我把它们都匹配起来
但似乎分数中没有考虑标签的数量
在测试这四个文档时：
- tags.put("doc1", "piano, electric guitar, violon");
- tags.put("doc2", "piano, electric guitar");
- tags.put("doc3", "piano");
- tags.put("doc4", "electric guitar");
我得到的是：
- Score : 1.0
Doc : Document<stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<id:doc4> stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<tag:electric guitar>>
- Score : 1.0
Doc : Document<stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<id:doc2> stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<tag:piano> stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<tag:electric guitar>>
- Score : 1.0
Doc : Document<stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<id:doc1> stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<tag:piano> stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<tag:electric guitar> stored,indexed,tokenized,omitNorms,indexOptions=DOCS_ONLY<tag:violon>>
我怎样才能改变这种行为？我是否错过了正确的做事方式
下面是我的测试代码
致以最良好的祝愿
雷诺
public class LuceneQueryTest {
Analyzer analyzer;
BasicIndex basicIndex;
LinkedList<String> phrases;
Query query;
Map<Document, Float> results;
@Test
public void testListOfTags() throws Exception {
analyzer = new StandardAnalyzer();
basicIndex = new BasicIndex(analyzer);
Map<String, String> tags = new HashMap();
tags.put("doc1", "piano, electric guitar, violon");
tags.put("doc2", "piano, electric guitar");
tags.put("doc3", "piano");
tags.put("doc4", "electric guitar");
Queue<String> queue = new LinkedList<>();
queue.addAll(tags.keySet());
basicIndex.index(new Supplier<Document>() {
public Document get() {
Document doc = new Document();
if (queue.isEmpty()) {
return null;
}
String docName = queue.poll();
System.out.println("**** "+docName);
String tag = tags.get(docName);
doc.add(new StringField("id", docName, Field.Store.YES));
for (String tagItem : tag.split("\\,")) {
System.out.println(tagItem);
Field tagField;
tagField = new StringField("tag",tagItem,Field.Store.YES);
System.out.println(tagField);
doc.add(tagField);
}
return doc;
}
});
BooleanQuery booleanQuery = new BooleanQuery();
//booleanQuery.add(new TermQuery(new Term("tag", "piano")), BooleanClause.Occur.SHOULD);
booleanQuery.add(new TermQuery(new Term("tag", "electric guitar")), BooleanClause.Occur.SHOULD);
//Query parsedQuery = new QueryParser("tag", analyzer).parse("tag:\"electric guitar\"");
query = booleanQuery;
//query = parsedQuery;
System.out.println(query);
results = basicIndex.search(query);
displayResults(results);
System.out.println(Arrays.toString(basicIndex.document(3).getValues("tag")));
}
private void displayResults(Map<Document, Float> results) {
results.forEach((Document doc, Float score) -> {
System.out.println("Score : " + score + " \n Doc : " + doc);
});
}
}
BasicIndex（测试实用程序）类的代码：
import java.io.IOException;
import java.util.LinkedHashMap;
import java.util.LinkedList;
import java.util.Map;
import java.util.function.Function;
import java.util.function.Supplier;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.document.TextField;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.IndexWriterConfig;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TopScoreDocCollector;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.RAMDirectory;
import org.apache.lucene.util.Version;
/**
*
* @author renaud
*/
public class BasicIndex {
final Directory directory = new RAMDirectory();
final IndexWriter indexWriter;
final Analyzer analyzer;
public BasicIndex(Analyzer analyzer) {
this.analyzer = analyzer;
this.indexWriter = newIndexWriter();
}
public Analyzer getAnalyzer() {
return analyzer;
}
private IndexWriter newIndexWriter() {
IndexWriterConfig config = new IndexWriterConfig(Version.LATEST, analyzer);
try {
return new IndexWriter(directory, config);
} catch (IOException ex) {
throw new RuntimeException(ex);
}
}
public IndexSearcher newIndexSearcher() {
return new IndexSearcher(newIndexReader());
}
public IndexReader newIndexReader() {
IndexReader reader;
try {
reader = DirectoryReader.open(directory);
} catch (IOException ex) {
throw ExceptionUtils.asRuntimeException(ex);
}
return reader;
}
public void index(LinkedList<String> phrases, final String fieldName) {
index(phrases, (String phrase) -> {
Document doc = new Document();
Field workField = new TextField(fieldName, phrase, Field.Store.YES);
doc.add(workField);
return doc;
});
}
public void index(Supplier<Document> documents) {
Document document;
while ((document = documents.get()) != null) {
try {
indexWriter.addDocument(document);
} catch (IOException e) {
throw ExceptionUtils.asRuntimeException(e);
}
}
close();
}
public void index(LinkedList<String> phrases, Function<String, Document> docBuilder) {
for (String phrase : phrases) {
try {
indexWriter.addDocument(docBuilder.apply(phrase));
} catch (IOException e) {
throw ExceptionUtils.asRuntimeException(e);
}
}
close();
}
private void close() {
IOUtils.closeSilently(indexWriter);
}
public Map<Document, Float> search(Query query) {
final IndexSearcher indexSearcher = newIndexSearcher();
int hitsPerPage = 10;
TopScoreDocCollector collector = TopScoreDocCollector.create(hitsPerPage, true);
try {
indexSearcher.search(query, collector);
} catch (IOException ex) {
throw new RuntimeException(ex);
}
ScoreDoc[] hits = collector.topDocs().scoreDocs;
Map<Document, Float> results = new LinkedHashMap<>();
for (int i = 0; i < hits.length; ++i) {
ScoreDoc scoreDoc = hits[i];
int docId = scoreDoc.doc;
float score = scoreDoc.score;
Document doc;
try {
doc = indexSearcher.doc(docId);
} catch (IOException ex) {
throw new RuntimeException(ex);
}
results.put(doc, score);
}
return results;
}
public Document document(int i){
try {
return newIndexSearcher().doc(i);
} catch (IOException ex) {
throw new RuntimeException(ex);
}
}
}
# 1 楼答案
好的，我最终得出的解决方案是：
我还发现SOLR是一个很好的关键字，可以在互联网上搜索Lucene的信息，因为它有更多的文档记录，同时还可以接近java代码
我对结果非常满意：
以及更新的代码：