// Test with BooleanQuery
        BooleanQuery.Builder builder = new BooleanQuery.Builder();
        Term term1 = new Term("content", "test");
        Term term2 = new Term("title", "query");
        builder.add(new TermQuery(term1), BooleanClause.Occur.SHOULD);
        builder.add(new TermQuery(term2), BooleanClause.Occur.SHOULD);
        BooleanQuery booleanQuery = builder.build();

     * Sets the maximum size of an alpha-numeric term.
     * @param maxAlphanumTermSize The max size of an alpha-numeric term.
     */
    public void setMaxAlphanumTermSize(final int maxAlphanumTermSize) {
        this.maxAlphanumTermSize = maxAlphanumTermSize;
    }

    /**
     * Sets the maximum size of a symbol term.
     * @param maxSymbolTermSize The max size of a symbol term.
     */

 *   <li>Optionally removing duplicate terms based on a flag.</li>
 *   <li>Limiting the maximum size of alphanumeric and symbol terms.</li>
 * </ul>
 *
 * <p>The {@link TextNormalizeContext} class provides a fluent API to configure the text
 * normalization process, including setting initial buffer capacity, maximum term sizes,
 * duplicate term removal, and custom space characters.
 *
 * <p>Example usage:

      any Contribution intentionally submitted for inclusion in the Work
      by You to the Licensor shall be under the terms and conditions of
      this License, without any additional terms or conditions.
      Notwithstanding the above, nothing herein shall supersede or modify
      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

            while (stream.incrementToken()) {
                final CharTermAttribute att = stream.getAttribute(CharTermAttribute.class);
                final String term = att.toString();
                final int pos = inputStr.indexOf(term, offset);
                if (pos > 0) {
                    final String tmp = inputStr.substring(offset, pos);
                    kanaBuf.append(transliterator.transliterate(tmp));

- **Multi-language Support**: Built-in support for Japanese text processing with Kuromoji analyzer
- **Popular Words Analytics**: Track and analyze frequently searched terms
- **Flexible Text Processing**: Configurable converters and normalizers for text transformation
- **OpenSearch Integration**: Seamless integration with OpenSearch/Elasticsearch clusters

      any Contribution intentionally submitted for inclusion in the Work
      by You to the Licensor shall be under the terms and conditions of
      this License, without any additional terms or conditions.
      Notwithstanding the above, nothing herein shall supersede or modify
      the terms of any separate license agreement you may have executed
      with Licensor regarding such Contributions.

        }

        private String convertToJapaneseReading(String term) {
            // Simple simulation of Japanese reading conversion
            if ("東京".equals(term)) {
                return "トウキョウ";
            } else if ("大阪".equals(term)) {
                return "オオサカ";
            } else {
                return term.toUpperCase();
            }
        }
    }

    /**

                    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) {

        int matchCount = 0;
        for (int i = 0; i < tokens.size(); i++) {
            final String term = tokens.get(i).getTerm();
            final String reading = readingTokens.get(i).getTerm();
            switch (term) {
            case "fess":
                matchCount++;
                assertEquals("fess", reading);
                break;
            case "検索":