private string[] QueryOverSingleWord <TDistance>(SuggestionField suggestionField, string word, SuggestionOptions options, TDistance sd)
where TDistance : IStringDistance
{
var min = options.Accuracy ?? SuggestionOptions.DefaultAccuracy;
var field = suggestionField.Name;
var pageSize = options.PageSize;
var morePopular = options.SortMode == SuggestionSortMode.Popularity;
int lengthWord = word.Length;
var ir = _searcher.IndexReader;
int freq = (ir != null && field != null) ? ir.DocFreq(new Term(FWord, word), _state) : 0;
int goalFreq = (morePopular && ir != null && field != null) ? freq : 0;
// if the word exists in the real index and we don't care for word frequency, return the word itself
if (!morePopular && freq > 0)
{
return(new[] { word });
}
var query = new BooleanQuery();
var alreadySeen = new HashSet <string>();
int ng = GetMin(lengthWord);
int max = ng + 1;
var table = GramsTable;
for (; ng <= max; ng++)
{
string[] grams = FormGrams(word, ng);
if (grams.Length == 0)
{
continue; // hmm
}
if (BoostStart > 0)
{
// should we boost prefixes?
Add(query, table[ng].Start, grams[0], BoostStart); // matches start of word
}
if (BoostEnd > 0)
{
// should we boost suffixes
Add(query, table[ng].End, grams[grams.Length - 1], BoostEnd); // matches end of word
}
for (int i = 0; i < grams.Length; i++)
{
Add(query, table[ng].Gram, grams[i]);
}
}
int maxHits = 10 * pageSize;
// System.out.println("Q: " + query);
ScoreDoc[] hits = _searcher.Search(query, null, maxHits, _state).ScoreDocs;
// System.out.println("HITS: " + hits.length());
var queue = new SuggestWordQueue(pageSize);
// go thru more than 'maxr' matches in case the distance filter triggers
int stop = Math.Min(hits.Length, maxHits);
var suggestedWord = new SuggestWord();
for (int i = 0; i < stop; i++)
{
suggestedWord.Term = _searcher.Doc(hits[i].Doc, _state).Get(FWord, _state); // get orig word
// don't suggest a word for itself, that would be silly
if (suggestedWord.Term.Equals(word, StringComparison.OrdinalIgnoreCase))
{
continue;
}
// edit distance
suggestedWord.Score = sd.GetDistance(word, suggestedWord.Term);
if (suggestedWord.Score < min)
{
continue;
}
if (ir != null && field != null)
{
// use the user index
suggestedWord.Freq = _searcher.DocFreq(new Term(FWord, suggestedWord.Term), _state); // freq in the index
// don't suggest a word that is not present in the field
if ((morePopular && goalFreq > suggestedWord.Freq) || suggestedWord.Freq < 1)
{
continue;
}
}
if (alreadySeen.Add(suggestedWord.Term) == false) // we already seen this word, no point returning it twice
{
continue;
}
queue.InsertWithOverflow(suggestedWord);
if (queue.Size() == pageSize)
{
// if queue full, maintain the minScore score
min = queue.Top().Score;
}
suggestedWord = new SuggestWord();
}
int size = queue.Size();
if (size == 0)
{
return(EmptyArray);
}
// convert to array string
string[] list = new string[size];
for (int i = size - 1; i >= 0; i--)
{
list[i] = queue.Pop().Term;
}
return(list);
}
/// <summary>
/// Suggest similar words (optionally restricted to a field of an index).
///
/// <para>As the Lucene similarity that is used to fetch the most relevant n-grammed terms
/// is not the same as the edit distance strategy used to calculate the best
/// matching spell-checked word from the hits that Lucene found, one usually has
/// to retrieve a couple of numSug's in order to get the true best match.
///
/// </para>
/// <para>I.e. if numSug == 1, don't count on that suggestion being the best one.
/// Thus, you should set this value to <b>at least</b> 5 for a good suggestion.
///
/// </para>
/// </summary>
/// <param name="word"> the word you want a spell check done on </param>
/// <param name="numSug"> the number of suggested words </param>
/// <param name="ir"> the indexReader of the user index (can be null see field param) </param>
/// <param name="field"> the field of the user index: if field is not null, the suggested
/// words are restricted to the words present in this field. </param>
/// <param name="suggestMode">
/// (NOTE: if indexReader==null and/or field==null, then this is overridden with SuggestMode.SUGGEST_ALWAYS) </param>
/// <param name="accuracy"> The minimum score a suggestion must have in order to qualify for inclusion in the results </param>
/// <exception cref="IOException"> if the underlying index throws an <seealso cref="IOException"/> </exception>
/// <exception cref="AlreadyClosedException"> if the Spellchecker is already closed </exception>
/// <returns> String[] the sorted list of the suggest words with these 2 criteria:
/// first criteria: the edit distance, second criteria (only if restricted mode): the popularity
/// of the suggest words in the field of the user index
/// </returns>
public virtual string[] SuggestSimilar(string word, int numSug, IndexReader ir, string field, SuggestMode suggestMode, float accuracy)
{
// obtainSearcher calls ensureOpen
IndexSearcher indexSearcher = ObtainSearcher();
try
{
if (ir == null || field == null)
{
suggestMode = SuggestMode.SUGGEST_ALWAYS;
}
if (suggestMode == SuggestMode.SUGGEST_ALWAYS)
{
ir = null;
field = null;
}
int lengthWord = word.Length;
int freq = (ir != null && field != null) ? ir.DocFreq(new Term(field, word)) : 0;
int goalFreq = suggestMode == SuggestMode.SUGGEST_MORE_POPULAR ? freq : 0;
// if the word exists in the real index and we don't care for word frequency, return the word itself
if (suggestMode == SuggestMode.SUGGEST_WHEN_NOT_IN_INDEX && freq > 0)
{
return new string[] { word };
}
BooleanQuery query = new BooleanQuery();
string[] grams;
string key;
for (int ng = GetMin(lengthWord); ng <= GetMax(lengthWord); ng++)
{
key = "gram" + ng; // form key
grams = FormGrams(word, ng); // form word into ngrams (allow dups too)
if (grams.Length == 0)
{
continue; // hmm
}
if (bStart > 0) // should we boost prefixes?
{
Add(query, "start" + ng, grams[0], bStart); // matches start of word
}
if (bEnd > 0) // should we boost suffixes
{
Add(query, "end" + ng, grams[grams.Length - 1], bEnd); // matches end of word
}
for (int i = 0; i < grams.Length; i++)
{
Add(query, key, grams[i]);
}
}
int maxHits = 10 * numSug;
// System.out.println("Q: " + query);
ScoreDoc[] hits = indexSearcher.Search(query, null, maxHits).ScoreDocs;
// System.out.println("HITS: " + hits.length());
SuggestWordQueue sugQueue = new SuggestWordQueue(numSug, comparator);
// go thru more than 'maxr' matches in case the distance filter triggers
int stop = Math.Min(hits.Length, maxHits);
SuggestWord sugWord = new SuggestWord();
for (int i = 0; i < stop; i++)
{
sugWord.@string = indexSearcher.Doc(hits[i].Doc).Get(F_WORD); // get orig word
// don't suggest a word for itself, that would be silly
if ([email protected](word))
{
continue;
}
// edit distance
sugWord.score = sd.GetDistance(word, sugWord.@string);
if (sugWord.score < accuracy)
{
continue;
}
if (ir != null && field != null) // use the user index
{
sugWord.freq = ir.DocFreq(new Term(field, sugWord.@string)); // freq in the index
// don't suggest a word that is not present in the field
if ((suggestMode == SuggestMode.SUGGEST_MORE_POPULAR && goalFreq > sugWord.freq) || sugWord.freq < 1)
{
continue;
}
}
sugQueue.InsertWithOverflow(sugWord);
if (sugQueue.Size() == numSug)
{
// if queue full, maintain the minScore score
accuracy = sugQueue.Top().score;
}
sugWord = new SuggestWord();
}
// convert to array string
string[] list = new string[sugQueue.Size()];
for (int i = sugQueue.Size() - 1; i >= 0; i--)
{
list[i] = sugQueue.Pop().@string;
}
return list;
}
finally
{
ReleaseSearcher(indexSearcher);
}
}
