/**
* Find words for a more-like-this query former.
*
* @param docNum the id of the lucene document from which to find terms
*/
private PriorityQueue<ScoreTerm> retrieveTerms(int docNum) throws IOException {
Map<String, Map<String, Int>> field2termFreqMap = new HashMap<>();
for (String fieldName : fieldNames) {
final Fields vectors = ir.getTermVectors(docNum);
final Terms vector;
if (vectors != null) {
vector = vectors.terms(fieldName);
} else {
vector = null;
}
// field does not store term vector info
if (vector == null) {
Document d = ir.document(docNum);
IndexableField[] fields = d.getFields(fieldName);
for (IndexableField field : fields) {
final String stringValue = field.stringValue();
if (stringValue != null) {
addTermFrequencies(new StringReader(stringValue), field2termFreqMap, fieldName);
}
}
} else {
addTermFrequencies(field2termFreqMap, vector, fieldName);
}
}
return createQueue(field2termFreqMap);
}
/**
* Return a query that will return docs like the passed Readers. This was added in order to treat
* multi-value fields.
*
* @return a query that will return docs like the passed Readers.
*/
public Query like(String fieldName, Reader... readers) throws IOException {
Map<String, Map<String, Int>> perFieldTermFrequencies = new HashMap<>();
for (Reader r : readers) {
addTermFrequencies(r, perFieldTermFrequencies, fieldName);
}
return createQuery(createQueue(perFieldTermFrequencies));
}
private PriorityQueue<ScoreTerm> retrieveTerms(Map<String, Collection<Object>> field2fieldValues)
throws IOException {
Map<String, Map<String, Int>> field2termFreqMap = new HashMap<>();
for (String fieldName : fieldNames) {
for (String field : field2fieldValues.keySet()) {
Collection<Object> fieldValues = field2fieldValues.get(field);
if (fieldValues == null) continue;
for (Object fieldValue : fieldValues) {
if (fieldValue != null) {
addTermFrequencies(
new StringReader(String.valueOf(fieldValue)), field2termFreqMap, fieldName);
}
}
}
}
return createQueue(field2termFreqMap);
}
/**
* Find words for a more-like-this query former. The result is a priority queue of arrays with one
* entry for <b>every word</b> in the document. Each array has 6 elements. The elements are:
*
* <ol>
* <li>The word (String)
* <li>The top field that this word comes from (String)
* <li>The score for this word (Float)
* <li>The IDF value (Float)
* <li>The frequency of this word in the index (Integer)
* <li>The frequency of this word in the source document (Integer)
* </ol>
*
* This is a somewhat "advanced" routine, and in general only the 1st entry in the array is of
* interest. This method is exposed so that you can identify the "interesting words" in a
* document. For an easier method to call see {@link #retrieveInterestingTerms
* retrieveInterestingTerms()}.
*
* @param r the reader that has the content of the document
* @param fieldName field passed to the analyzer to use when analyzing the content
* @return the most interesting words in the document ordered by score, with the highest scoring,
* or best entry, first
* @see #retrieveInterestingTerms
*/
private PriorityQueue<ScoreTerm> retrieveTerms(Reader r, String fieldName) throws IOException {
Map<String, Map<String, Int>> field2termFreqMap = new HashMap<>();
addTermFrequencies(r, field2termFreqMap, fieldName);
return createQueue(field2termFreqMap);
}
/**
* Find words for a more-like-this query former. The result is a priority queue of arrays with one
* entry for <b>every word</b> in the document. Each array has 6 elements. The elements are:
*
* <ol>
* <li>The word (String)
* <li>The top field that this word comes from (String)
* <li>The score for this word (Float)
* <li>The IDF value (Float)
* <li>The frequency of this word in the index (Integer)
* <li>The frequency of this word in the source document (Integer)
* </ol>
*
* This is a somewhat "advanced" routine, and in general only the 1st entry in the array is of
* interest. This method is exposed so that you can identify the "interesting words" in a
* document. For an easier method to call see {@link #retrieveInterestingTerms
* retrieveInterestingTerms()}.
*
* @param r the reader that has the content of the document
* @param fieldName field passed to the analyzer to use when analyzing the content
* @return the most interesting words in the document ordered by score, with the highest scoring,
* or best entry, first
* @see #retrieveInterestingTerms
*/
private PriorityQueue<ScoreTerm> retrieveTerms(Reader r, String fieldName) throws IOException {
Map<String, Int> words = new HashMap<>();
addTermFrequencies(r, words, fieldName);
return createQueue(words);
}
