在Apache Lucene 7.5.x中，可以使用TF-IDF（Term Frequency-Inverse Document Frequency）来计算文档之间的相关性和相似性。下面是一个简单的代码示例：

首先，你需要创建一个IndexWriter对象，并将文档添加到索引中：

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.document.TextField;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.IndexWriterConfig;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.util.Version;

import java.io.IOException;
import java.nio.file.Paths;

public class Indexer {

    private final Directory directory;
    private final Analyzer analyzer;

    public Indexer(String indexDirectoryPath) throws IOException {
        directory = FSDirectory.open(Paths.get(indexDirectoryPath));
        analyzer = new StandardAnalyzer();
    }

    public void createIndex(String dataDirectoryPath) throws IOException {
        IndexWriterConfig config = new IndexWriterConfig(analyzer);
        IndexWriter writer = new IndexWriter(directory, config);
        File[] files = new File(dataDirectoryPath).listFiles();

        for (File file : files) {
            Document document = new Document();
            String content = FileUtils.readFileToString(file, "UTF-8");
            document.add(new TextField("content", content, Field.Store.YES));
            writer.addDocument(document);
        }

        writer.close();
    }

    public static void main(String[] args) throws IOException {
        String indexDirectoryPath = "path/to/index";
        String dataDirectoryPath = "path/to/data";

        Indexer indexer = new Indexer(indexDirectoryPath);
        indexer.createIndex(dataDirectoryPath);
    }
}

接下来，你可以使用IndexSearcher来搜索索引并计算文档之间的相关性和相似性：

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.queryparser.classic.ParseException;
import org.apache.lucene.queryparser.classic.QueryParser;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.FSDirectory;

import java.io.IOException;
import java.nio.file.Paths;

public class Searcher {

    private final IndexSearcher indexSearcher;
    private final QueryParser queryParser;

    public Searcher(String indexDirectoryPath) throws IOException {
        Directory directory = FSDirectory.open(Paths.get(indexDirectoryPath));
        IndexReader reader = DirectoryReader.open(directory);
        indexSearcher = new IndexSearcher(reader);
        Analyzer analyzer = new StandardAnalyzer();
        queryParser = new QueryParser("content", analyzer);
    }

    public TopDocs search(String searchQuery) throws IOException, ParseException {
        Query query = queryParser.parse(searchQuery);
        return indexSearcher.search(query, 10);
    }

    public Document getDocument(ScoreDoc scoreDoc) throws IOException {
        return indexSearcher.doc(scoreDoc.doc);
    }

    public static void main(String[] args) throws IOException, ParseException {
        String indexDirectoryPath = "path/to/index";

        Searcher searcher = new Searcher(indexDirectoryPath);
        TopDocs topDocs = searcher.search("your search query");

        for (ScoreDoc scoreDoc : topDocs.scoreDocs) {
            Document document = searcher.getDocument(scoreDoc);
            System.out.println("Document: " + document.getField("content").stringValue());
            System.out.println("Score: " + scoreDoc.score);
        }
    }
}

以上代码示例演示了如何创建索引并进行搜索，然后输出搜索结果的文档内容和相关性得分。你可以根据自己的需求进行修改和扩展。