super(term, position, startOffset, endOffset, positionIncrement, type, attributes);
        }

        public String getReading() {
            return reading;
        }

        public void setReading(String reading) {
            this.reading = reading;
        }
    }

    /** Key for elevate word boost. */
    public static final String ELEVATE_WORD_BOOST = "boost";
    /** Key for elevate word reading. */
    public static final String ELEVATE_WORD_READING = "reading";
    /** Key for elevate word fields. */
    public static final String ELEVATE_WORD_FIELDS = "fields";
    /** Key for elevate word tags. */

                    final String term = termTokenList.get(i).getTerm();
                    String reading = readingTokenList.get(i).getTerm();
                    if (Strings.isNullOrEmpty(reading)) {
                        reading = term;
                    }
                    reading = transliterator.transliterate(reading);

                    final int pos = text.indexOf(term, offset);
                    if (pos > 0) {

    public void setUserBoost(final float userBoost) {
        this.userBoost = userBoost;
    }

    /**
     * Sets the readings of the suggest item.
     * @param readings The readings to set.
     */
    public void setReadings(final String[][] readings) {
        this.readings = readings;
    }

    /**
     * Sets the fields of the suggest item.
     * @param fields The fields to set.
     */

    }

    /**
     * Sets the reading converter.
     * @param readingConverter The reading converter.
     * @return This builder instance.
     */
    public SuggesterBuilder readingConverter(final ReadingConverter readingConverter) {
        this.readingConverter = readingConverter;
        return this;
    }

    /**
     * Sets the contents reading converter.

/**
 * <p>
 * {@link ESSourceReader} reads documents from Elasticsearch using the scroll API.
 * It implements the {@link DocumentReader} interface to provide a way to iterate over documents
 * in a large index without loading all of them into memory at once.
 * </p>
 *
 * <p>
 * The reader supports limiting the number of documents read based on a percentage of the total documents

        final Map<String, Object> secondLine = new HashMap<>();

        secondLine.put("text", item.getText());

        // reading
        final String[][] readings = item.getReadings();
        for (int i = 0; i < readings.length; i++) {
            secondLine.put("reading_" + i, readings[i]);
        }

        secondLine.put("fields", item.getFields());
        secondLine.put("queryFreq", item.getQueryFreq());

 *       normalization, contents, and contents reading) for a specific field.</li>
 * </ul>
 *
 * @see SuggestAnalyzer
 * @see FieldAnalyzerMapping
 */
public class AnalyzerSettings {
    /** Analyzer name for reading. */
    public static final String READING_ANALYZER = "reading_analyzer";
    /** Analyzer name for reading term. */

 * A chain of {@link ReadingConverter} implementations that applies each converter in sequence to generate possible reading variations of a given text.
 * It maintains a list of ReadingConverter instances and iterates through them, applying each converter to the input text and accumulating the results.
 * The chain stops processing when the maximum number of readings is reached.
 */
public class ReadingConverterChain implements ReadingConverter {
    /**

 */
package org.codelibs.fess.suggest.index.contents.document;

import java.io.Closeable;
import java.util.Map;

/**
 * Interface for reading documents and extracting their contents into a map.
 * Implementations of this interface should provide the logic for reading
 * documents and converting them into a key-value structure.
 *
 * <p>This interface extends {@link java.io.Closeable}, so implementations