Lucene中的术语文档矩阵 [英] Term-document matrix in Lucene

问题描述

我正在尝试从Lucene获取术语文档矩阵.似乎大多数SO问题都针对具有不同类的过时API.我尝试将这两个问题的见解相结合，以从每个文档中获取术语向量:

I am trying to get a term-document matrix from Lucene. It seems that most of the SO questions are for outdated APIs with different classes. I tried combining insight from these two questions to get a term vector from every document:

• Lucene 4.0中的术语向量频率
• 可以遍历文档存储在Lucene Index中?

相关代码，但是在当前API中无法识别 DocEnum .如何获得每个文档的术语向量或所有术语的计数?

Relevant code, but DocEnum is not recognized in the current API. How can I get a term vector or count of all terms for every document?

IndexReader reader = DirectoryReader.open(index);

for (int i = 0;  i < reader.maxDoc(); i++) {
    Document doc = reader.document(i);
    Terms terms = reader.getTermVector(i, "country_text");

    if (terms != null && terms.size() > 0) {
        // access the terms for this field
        TermsEnum termsEnum = terms.iterator(); 
        BytesRef term = null;

        // explore the terms for this field
        while ((term = termsEnum.next()) != null) {
            // enumerate through documents, in this case only one
            DocsEnum docsEnum = termsEnum.docs(null, null); 
            int docIdEnum;
            while ((docIdEnum = docsEnum.nextDoc()) != DocIdSetIterator.NO_MORE_DOCS) {
                // get the term frequency in the document 
                System.out.println(term.utf8ToString()+ " " + docIdEnum + " " + docsEnum.freq()); 
            }
        }
    }
}

完整代码:

import java.io.*;
import java.util.Iterator;

import org.apache.lucene.analysis.standard.StandardAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.document.StringField;
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.index.Term;
import org.apache.lucene.index.Terms;
import org.apache.lucene.index.TermsEnum;
import org.apache.lucene.queryparser.classic.ParseException;
import org.apache.lucene.queryparser.classic.QueryParser;
import org.apache.lucene.search.BooleanClause;
import org.apache.lucene.search.BooleanQuery;
import org.apache.lucene.search.FuzzyQuery;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TermQuery;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.RAMDirectory;
import org.apache.lucene.util.BytesRef;
import org.json.simple.JSONArray;
import org.json.simple.JSONObject;
import org.json.simple.JSONValue;
import org.json.simple.parser.JSONParser;

public class LuceneIndex {

    public static void main(String[] args) throws IOException, ParseException {

        String jsonFilePath = "wiki_data.json";
        JSONParser parser = new JSONParser();
        // Specify the analyzer for tokenizing text.
        StandardAnalyzer analyzer = new StandardAnalyzer();
        // create the index
        Directory index = new RAMDirectory();
        IndexWriterConfig config = new IndexWriterConfig(analyzer);
        IndexWriter w = new IndexWriter(index, config);

        try {     
            JSONArray a = (JSONArray) parser.parse(new FileReader(jsonFilePath));

            for (Object o : a) {
                JSONObject country = (JSONObject) o;
                String countryName = (String) country.get("country_name");
                String cityName = (String) country.get("city_name");
                String countryText = (String) country.get("country_text");
                String cityText = (String) country.get("city_text");
                System.out.println(cityName);
                addDoc(w, countryName, cityName, countryText, cityText);
            }
            w.close();

            IndexReader reader = DirectoryReader.open(index);

            for (int i = 0;  i < reader.maxDoc(); i++) {
                Document doc = reader.document(i);
                Terms terms = reader.getTermVector(i, "country_text");

                if (terms != null && terms.size() > 0) {
                    // access the terms for this field
                    TermsEnum termsEnum = terms.iterator(); 
                    BytesRef term = null;

                    // explore the terms for this field
                    while ((term = termsEnum.next()) != null) {
                        // enumerate through documents, in this case only one
                        DocsEnum docsEnum = termsEnum.docs(null, null); 
                        int docIdEnum;
                        while ((docIdEnum = docsEnum.nextDoc()) != DocIdSetIterator.NO_MORE_DOCS) {
                            // get the term frequency in the document 
                            System.out.println(term.utf8ToString()+ " " + docIdEnum + " " + docsEnum.freq()); 
                        }
                    }
                }
            }

            // reader can be closed when there
            // is no need to access the documents any more.
            reader.close();

        } catch (FileNotFoundException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        } catch (org.json.simple.parser.ParseException e) {
            e.printStackTrace();
        }
    }

    private static void addDoc(IndexWriter w, String countryName, String cityName, 
            String countryText, String cityText) throws IOException {
        Document doc = new Document();
        doc.add(new StringField("country_name", countryName, Field.Store.YES));
        doc.add(new StringField("city_name", cityName, Field.Store.YES));
        doc.add(new TextField("country_text", countryText, Field.Store.YES));
        doc.add(new TextField("city_text", cityText, Field.Store.YES));

        w.addDocument(doc);
    }

}

推荐答案

首先感谢您的代码，我有一个小错误，您的代码帮助我完成了它.

First thank for your code I had a little bug and your code helped me to complete it.

对我来说，它适用于:(Lucene 7.2.1)

For me it works with this: (Lucene 7.2.1)

for(int i = 0; i < reader.maxDoc(); i++){
    Document doc = reader.document(i);
    Terms terms = reader.getTermVector(i, "text");

    if (terms != null && terms.size() > 0) {
        // access the terms for this field
        TermsEnum termsEnum = terms.iterator();
        BytesRef term = null;

        // explore the terms for this field
        while ((term = termsEnum.next()) != null) {
            // enumerate through documents, in this case only one
            PostingsEnum docsEnum = termsEnum.postings(null); 
            int docIdEnum;
            while ((docIdEnum = docsEnum.nextDoc()) != DocIdSetIterator.NO_MORE_DOCS) {
                // get the term frequency in the document
                System.out.println(term.utf8ToString()+ " " + docIdEnum + " " + docsEnum.freq());
            }
        }
    }
}

这里的更改是我使用PostingsEnum.DocsEnum在Lucene 7.2.1中不再可用.

The Change here is I used PostingsEnum. DocsEnum is not available in Lucene 7.2.1 anymore.

但是为什么对您不起作用，是您添加文档的方式:

But why it didn't work for you is how you add your document:

private void addDoc(IndexWriter w, String text, String name, String id) throws IOException {
    Document doc = new Document();
    // Create own FieldType to store Term Vectors
    FieldType ft = new FieldType();
    ft.setIndexOptions(IndexOptions.DOCS_AND_FREQS);
    ft.setTokenized(true);
    ft.setStored(true);
    ft.setStoreTermVectors(true);  //Store Term Vectors
    ft.freeze();
    StoredField t = new StoredField("text",text,ft);
    doc.add(t);


    doc.add(new StringField("name", name, Field.Store.YES));
    doc.add(new StringField("id", id, Field.Store.YES));
    w.addDocument(doc);
}

您必须创建自己的FieldType.没有一个标准的会保存术语向量.

You have to create your own FieldType. None of the standard ones will save the term vectors.

这篇关于Lucene中的术语文档矩阵的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！