How to auto-fill / suggest a query in Lucene?

I am looking for a way to do autocomplete / query suggestions in Lucene. I ruined a little and played a little, but all the examples that I saw seem to configure filters in Solr. We are not using Solr, and we are not planning to move on to using Solr in the near future, and Solr obviously just wraps around Lucene, so I suppose there should be a way to do this!

I studied the use of EdgeNGramFilter, and I understand that I will need to run the filter in the index fields and get the tokens, and then compare them with the Query entered ... I'm just trying to make the connection between them in a bit of code, so help is really appreciated!

To understand what Iโ€™m looking for (I realized that Iโ€™m not too clear, sorry) - Iโ€™m looking for a solution where, when searching for a term, it will return a list of suggested queries, When you enter โ€œinterโ€ in the search field, it will return with a list of suggested queries, such as "Internet", "International", etc.

+47
java autocomplete lucene
Sep 23 '08 at 10:12
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5 answers

Based on @Alexandre Victoor's answer, I wrote a small class based on Lucene Spellchecker in the contrib package (and using the LuceneDictionary included in it) that does exactly what I want.

This allows you to re-index a single field index from a single source and offers suggestions for terms. Results are sorted by the number of matching documents with this term in the source index, so more popular terms first appear. It seems to work very well :)

import java.io.IOException; import java.io.Reader; import java.util.ArrayList; import java.util.HashMap; import java.util.Iterator; import java.util.List; import java.util.Map; import org.apache.lucene.analysis.Analyzer; import org.apache.lucene.analysis.ISOLatin1AccentFilter; import org.apache.lucene.analysis.LowerCaseFilter; import org.apache.lucene.analysis.StopFilter; import org.apache.lucene.analysis.TokenStream; import org.apache.lucene.analysis.ngram.EdgeNGramTokenFilter; import org.apache.lucene.analysis.ngram.EdgeNGramTokenFilter.Side; import org.apache.lucene.analysis.standard.StandardFilter; import org.apache.lucene.analysis.standard.StandardTokenizer; import org.apache.lucene.document.Document; import org.apache.lucene.document.Field; import org.apache.lucene.index.CorruptIndexException; import org.apache.lucene.index.IndexReader; import org.apache.lucene.index.IndexWriter; import org.apache.lucene.index.Term; import org.apache.lucene.search.IndexSearcher; import org.apache.lucene.search.Query; import org.apache.lucene.search.ScoreDoc; import org.apache.lucene.search.Sort; import org.apache.lucene.search.TermQuery; import org.apache.lucene.search.TopDocs; import org.apache.lucene.search.spell.LuceneDictionary; import org.apache.lucene.store.Directory; import org.apache.lucene.store.FSDirectory; /** * Search term auto-completer, works for single terms (so use on the last term * of the query). * <p> * Returns more popular terms first. * * @author Mat Mannion, M.Mannion@warwick.ac.uk */ public final class Autocompleter { private static final String GRAMMED_WORDS_FIELD = "words"; private static final String SOURCE_WORD_FIELD = "sourceWord"; private static final String COUNT_FIELD = "count"; private static final String[] ENGLISH_STOP_WORDS = { "a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "i", "if", "in", "into", "is", "no", "not", "of", "on", "or", "s", "such", "t", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with" }; private final Directory autoCompleteDirectory; private IndexReader autoCompleteReader; private IndexSearcher autoCompleteSearcher; public Autocompleter(String autoCompleteDir) throws IOException { this.autoCompleteDirectory = FSDirectory.getDirectory(autoCompleteDir, null); reOpenReader(); } public List<String> suggestTermsFor(String term) throws IOException { // get the top 5 terms for query Query query = new TermQuery(new Term(GRAMMED_WORDS_FIELD, term)); Sort sort = new Sort(COUNT_FIELD, true); TopDocs docs = autoCompleteSearcher.search(query, null, 5, sort); List<String> suggestions = new ArrayList<String>(); for (ScoreDoc doc : docs.scoreDocs) { suggestions.add(autoCompleteReader.document(doc.doc).get( SOURCE_WORD_FIELD)); } return suggestions; } @SuppressWarnings("unchecked") public void reIndex(Directory sourceDirectory, String fieldToAutocomplete) throws CorruptIndexException, IOException { // build a dictionary (from the spell package) IndexReader sourceReader = IndexReader.open(sourceDirectory); LuceneDictionary dict = new LuceneDictionary(sourceReader, fieldToAutocomplete); // code from // org.apache.lucene.search.spell.SpellChecker.indexDictionary( // Dictionary) IndexReader.unlock(autoCompleteDirectory); // use a custom analyzer so we can do EdgeNGramFiltering IndexWriter writer = new IndexWriter(autoCompleteDirectory, new Analyzer() { public TokenStream tokenStream(String fieldName, Reader reader) { TokenStream result = new StandardTokenizer(reader); result = new StandardFilter(result); result = new LowerCaseFilter(result); result = new ISOLatin1AccentFilter(result); result = new StopFilter(result, ENGLISH_STOP_WORDS); result = new EdgeNGramTokenFilter( result, Side.FRONT,1, 20); return result; } }, true); writer.setMergeFactor(300); writer.setMaxBufferedDocs(150); // go through every word, storing the original word (incl. n-grams) // and the number of times it occurs Map<String, Integer> wordsMap = new HashMap<String, Integer>(); Iterator<String> iter = (Iterator<String>) dict.getWordsIterator(); while (iter.hasNext()) { String word = iter.next(); int len = word.length(); if (len < 3) { continue; // too short we bail but "too long" is fine... } if (wordsMap.containsKey(word)) { throw new IllegalStateException( "This should never happen in Lucene 2.3.2"); // wordsMap.put(word, wordsMap.get(word) + 1); } else { // use the number of documents this word appears in wordsMap.put(word, sourceReader.docFreq(new Term( fieldToAutocomplete, word))); } } for (String word : wordsMap.keySet()) { // ok index the word Document doc = new Document(); doc.add(new Field(SOURCE_WORD_FIELD, word, Field.Store.YES, Field.Index.UN_TOKENIZED)); // orig term doc.add(new Field(GRAMMED_WORDS_FIELD, word, Field.Store.YES, Field.Index.TOKENIZED)); // grammed doc.add(new Field(COUNT_FIELD, Integer.toString(wordsMap.get(word)), Field.Store.NO, Field.Index.UN_TOKENIZED)); // count writer.addDocument(doc); } sourceReader.close(); // close writer writer.optimize(); writer.close(); // re-open our reader reOpenReader(); } private void reOpenReader() throws CorruptIndexException, IOException { if (autoCompleteReader == null) { autoCompleteReader = IndexReader.open(autoCompleteDirectory); } else { autoCompleteReader.reopen(); } autoCompleteSearcher = new IndexSearcher(autoCompleteReader); } public static void main(String[] args) throws Exception { Autocompleter autocomplete = new Autocompleter("/index/autocomplete"); // run this to re-index from the current index, shouldn't need to do // this very often // autocomplete.reIndex(FSDirectory.getDirectory("/index/live", null), // "content"); String term = "steve"; System.out.println(autocomplete.suggestTermsFor(term)); // prints [steve, steven, stevens, stevenson, stevenage] } } 
+37
Sep 23 '08 at 14:41
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Here's a transliteration of the Mat implementation in C # for Lucene.NET, as well as a snippet for connecting a text field using the jQuery autocomplete function.

 <input id="search-input" name="query" placeholder="Search database." type="text" /> 

... jquery autocomplete:

 // don't navigate away from the field when pressing tab on a selected item $( "#search-input" ).keydown(function (event) { if (event.keyCode === $.ui.keyCode.TAB && $(this).data("autocomplete").menu.active) { event.preventDefault(); } }); $( "#search-input" ).autocomplete({ source: '@Url.Action("SuggestTerms")', // <-- ASP.NET MVC Razor syntax minLength: 2, delay: 500, focus: function () { // prevent value inserted on focus return false; }, select: function (event, ui) { var terms = this.value.split(/\s+/); terms.pop(); // remove dropdown item terms.push(ui.item.value.trim()); // add completed item this.value = terms.join(" "); return false; }, }); 

... here is the ASP.NET MVC controller code:

  // // GET: /MyApp/SuggestTerms?term=something public JsonResult SuggestTerms(string term) { if (string.IsNullOrWhiteSpace(term)) return Json(new string[] {}); term = term.Split().Last(); // Fetch suggestions string[] suggestions = SearchSvc.SuggestTermsFor(term).ToArray(); return Json(suggestions, JsonRequestBehavior.AllowGet); } 

... and here's the Matt code in C #:

 using System; using System.Collections.Generic; using System.Linq; using System.Text; using Lucene.Net.Store; using Lucene.Net.Index; using Lucene.Net.Search; using SpellChecker.Net.Search.Spell; using Lucene.Net.Analysis; using Lucene.Net.Analysis.Standard; using Lucene.Net.Analysis.NGram; using Lucene.Net.Documents; namespace Cipher.Services { /// <summary> /// Search term auto-completer, works for single terms (so use on the last term of the query). /// Returns more popular terms first. /// <br/> /// Author: Mat Mannion, M.Mannion@warwick.ac.uk /// <seealso cref="http://stackoverflow.com/questions/120180/how-to-do-query-auto-completion-suggestions-in-lucene"/> /// </summary> /// public class SearchAutoComplete { public int MaxResults { get; set; } private class AutoCompleteAnalyzer : Analyzer { public override TokenStream TokenStream(string fieldName, System.IO.TextReader reader) { TokenStream result = new StandardTokenizer(kLuceneVersion, reader); result = new StandardFilter(result); result = new LowerCaseFilter(result); result = new ASCIIFoldingFilter(result); result = new StopFilter(false, result, StopFilter.MakeStopSet(kEnglishStopWords)); result = new EdgeNGramTokenFilter( result, Lucene.Net.Analysis.NGram.EdgeNGramTokenFilter.DEFAULT_SIDE,1, 20); return result; } } private static readonly Lucene.Net.Util.Version kLuceneVersion = Lucene.Net.Util.Version.LUCENE_29; private static readonly String kGrammedWordsField = "words"; private static readonly String kSourceWordField = "sourceWord"; private static readonly String kCountField = "count"; private static readonly String[] kEnglishStopWords = { "a", "an", "and", "are", "as", "at", "be", "but", "by", "for", "i", "if", "in", "into", "is", "no", "not", "of", "on", "or", "s", "such", "t", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with" }; private readonly Directory m_directory; private IndexReader m_reader; private IndexSearcher m_searcher; public SearchAutoComplete(string autoCompleteDir) : this(FSDirectory.Open(new System.IO.DirectoryInfo(autoCompleteDir))) { } public SearchAutoComplete(Directory autoCompleteDir, int maxResults = 8) { this.m_directory = autoCompleteDir; MaxResults = maxResults; ReplaceSearcher(); } /// <summary> /// Find terms matching the given partial word that appear in the highest number of documents.</summary> /// <param name="term">A word or part of a word</param> /// <returns>A list of suggested completions</returns> public IEnumerable<String> SuggestTermsFor(string term) { if (m_searcher == null) return new string[] { }; // get the top terms for query Query query = new TermQuery(new Term(kGrammedWordsField, term.ToLower())); Sort sort = new Sort(new SortField(kCountField, SortField.INT)); TopDocs docs = m_searcher.Search(query, null, MaxResults, sort); string[] suggestions = docs.ScoreDocs.Select(doc => m_reader.Document(doc.Doc).Get(kSourceWordField)).ToArray(); return suggestions; } /// <summary> /// Open the index in the given directory and create a new index of word frequency for the /// given index.</summary> /// <param name="sourceDirectory">Directory containing the index to count words in.</param> /// <param name="fieldToAutocomplete">The field in the index that should be analyzed.</param> public void BuildAutoCompleteIndex(Directory sourceDirectory, String fieldToAutocomplete) { // build a dictionary (from the spell package) using (IndexReader sourceReader = IndexReader.Open(sourceDirectory, true)) { LuceneDictionary dict = new LuceneDictionary(sourceReader, fieldToAutocomplete); // code from // org.apache.lucene.search.spell.SpellChecker.indexDictionary( // Dictionary) //IndexWriter.Unlock(m_directory); // use a custom analyzer so we can do EdgeNGramFiltering var analyzer = new AutoCompleteAnalyzer(); using (var writer = new IndexWriter(m_directory, analyzer, true, IndexWriter.MaxFieldLength.LIMITED)) { writer.MergeFactor = 300; writer.SetMaxBufferedDocs(150); // go through every word, storing the original word (incl. n-grams) // and the number of times it occurs foreach (string word in dict) { if (word.Length < 3) continue; // too short we bail but "too long" is fine... // ok index the word // use the number of documents this word appears in int freq = sourceReader.DocFreq(new Term(fieldToAutocomplete, word)); var doc = MakeDocument(fieldToAutocomplete, word, freq); writer.AddDocument(doc); } writer.Optimize(); } } // re-open our reader ReplaceSearcher(); } private static Document MakeDocument(String fieldToAutocomplete, string word, int frequency) { var doc = new Document(); doc.Add(new Field(kSourceWordField, word, Field.Store.YES, Field.Index.NOT_ANALYZED)); // orig term doc.Add(new Field(kGrammedWordsField, word, Field.Store.YES, Field.Index.ANALYZED)); // grammed doc.Add(new Field(kCountField, frequency.ToString(), Field.Store.NO, Field.Index.NOT_ANALYZED)); // count return doc; } private void ReplaceSearcher() { if (IndexReader.IndexExists(m_directory)) { if (m_reader == null) m_reader = IndexReader.Open(m_directory, true); else m_reader.Reopen(); m_searcher = new IndexSearcher(m_reader); } else { m_searcher = null; } } } } 
+25
Feb 07 '12 at 20:32
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my code based on lucene 4.2 can help you

 import java.io.File; import java.io.IOException; import org.apache.lucene.analysis.miscellaneous.PerFieldAnalyzerWrapper; import org.apache.lucene.index.DirectoryReader; import org.apache.lucene.index.IndexWriterConfig; import org.apache.lucene.index.IndexWriterConfig.OpenMode; import org.apache.lucene.search.spell.Dictionary; import org.apache.lucene.search.spell.LuceneDictionary; import org.apache.lucene.search.spell.PlainTextDictionary; import org.apache.lucene.search.spell.SpellChecker; import org.apache.lucene.store.Directory; import org.apache.lucene.store.FSDirectory; import org.apache.lucene.store.IOContext; import org.apache.lucene.store.RAMDirectory; import org.apache.lucene.util.Version; import org.wltea4pinyin.analyzer.lucene.IKAnalyzer4PinYin; /** * * * @author <a href="mailto:liu.gang@renren-inc.com"></a> * @version 2013-11-25ไธŠๅˆ11:13:59 */ public class LuceneSpellCheckerDemoService { private static final String INDEX_FILE = "/Users/r/Documents/jar/luke/youtui/index"; private static final String INDEX_FILE_SPELL = "/Users/r/Documents/jar/luke/spell"; private static final String INDEX_FIELD = "app_name_quanpin"; public static void main(String args[]) { try { // PerFieldAnalyzerWrapper wrapper = new PerFieldAnalyzerWrapper(new IKAnalyzer4PinYin( true)); // read index conf IndexWriterConfig conf = new IndexWriterConfig(Version.LUCENE_42, wrapper); conf.setOpenMode(OpenMode.CREATE_OR_APPEND); // read dictionary Directory directory = FSDirectory.open(new File(INDEX_FILE)); RAMDirectory ramDir = new RAMDirectory(directory, IOContext.READ); DirectoryReader indexReader = DirectoryReader.open(ramDir); Dictionary dic = new LuceneDictionary(indexReader, INDEX_FIELD); SpellChecker sc = new SpellChecker(FSDirectory.open(new File(INDEX_FILE_SPELL))); //sc.indexDictionary(new PlainTextDictionary(new File("myfile.txt")), conf, false); sc.indexDictionary(dic, conf, true); String[] strs = sc.suggestSimilar("zhsiwusdazhanjiangshi", 10); for (int i = 0; i < strs.length; i++) { System.out.println(strs[i]); } sc.close(); } catch (IOException e) { e.printStackTrace(); } } } 
+5
Nov 26 '13 at 6:20
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You can use the PrefixQuery class by the dictionary index. The LuceneDictionary class can also be useful.

Take a look at this related article below. It explains how to implement the "Did you mean?" available on modern search engines such as Google. You may not need something complicated, as described in the article. However, the article explains how to use the Lucene Spell Pack.

One way to create a dictionary index is to iterate over LuceneDictionary.

Hope help

Did you mean Lucene? (Page 1)

Did you mean Lucene? (page 2)

Did you mean Lucene? (page 3)

+4
Sep 23 '08 at 11:31
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In addition to the above (highly rated) post re: C # conversion, if you are using .NET 3.5, you will need to enable the code for EdgeNGramTokenFilter - or at least I did - using Lucene 2.9.2 - as far as I know The filter is missing in the .NET version. I needed to find the version of .NET 4 on the Internet in 2.9.3 and return the port - I hope this makes the procedure less painful for someone ...

Edit: also note that the array returned by the SuggestTermsFor () function is sorted in ascending order by account, you probably want to cancel it to get the most popular terms first in your list

 using System.IO; using System.Collections; using Lucene.Net.Analysis; using Lucene.Net.Analysis.Tokenattributes; using Lucene.Net.Util; namespace Lucene.Net.Analysis.NGram { /** * Tokenizes the given token into n-grams of given size(s). * <p> * This {@link TokenFilter} create n-grams from the beginning edge or ending edge of a input token. * </p> */ public class EdgeNGramTokenFilter : TokenFilter { public static Side DEFAULT_SIDE = Side.FRONT; public static int DEFAULT_MAX_GRAM_SIZE = 1; public static int DEFAULT_MIN_GRAM_SIZE = 1; // Replace this with an enum when the Java 1.5 upgrade is made, the impl will be simplified /** Specifies which side of the input the n-gram should be generated from */ public class Side { private string label; /** Get the n-gram from the front of the input */ public static Side FRONT = new Side("front"); /** Get the n-gram from the end of the input */ public static Side BACK = new Side("back"); // Private ctor private Side(string label) { this.label = label; } public string getLabel() { return label; } // Get the appropriate Side from a string public static Side getSide(string sideName) { if (FRONT.getLabel().Equals(sideName)) { return FRONT; } else if (BACK.getLabel().Equals(sideName)) { return BACK; } return null; } } private int minGram; private int maxGram; private Side side; private char[] curTermBuffer; private int curTermLength; private int curGramSize; private int tokStart; private TermAttribute termAtt; private OffsetAttribute offsetAtt; protected EdgeNGramTokenFilter(TokenStream input) : base(input) { this.termAtt = (TermAttribute)AddAttribute(typeof(TermAttribute)); this.offsetAtt = (OffsetAttribute)AddAttribute(typeof(OffsetAttribute)); } /** * Creates EdgeNGramTokenFilter that can generate n-grams in the sizes of the given range * * @param input {@link TokenStream} holding the input to be tokenized * @param side the {@link Side} from which to chop off an n-gram * @param minGram the smallest n-gram to generate * @param maxGram the largest n-gram to generate */ public EdgeNGramTokenFilter(TokenStream input, Side side, int minGram, int maxGram) : base(input) { if (side == null) { throw new System.ArgumentException("sideLabel must be either front or back"); } if (minGram < 1) { throw new System.ArgumentException("minGram must be greater than zero"); } if (minGram > maxGram) { throw new System.ArgumentException("minGram must not be greater than maxGram"); } this.minGram = minGram; this.maxGram = maxGram; this.side = side; this.termAtt = (TermAttribute)AddAttribute(typeof(TermAttribute)); this.offsetAtt = (OffsetAttribute)AddAttribute(typeof(OffsetAttribute)); } /** * Creates EdgeNGramTokenFilter that can generate n-grams in the sizes of the given range * * @param input {@link TokenStream} holding the input to be tokenized * @param sideLabel the name of the {@link Side} from which to chop off an n-gram * @param minGram the smallest n-gram to generate * @param maxGram the largest n-gram to generate */ public EdgeNGramTokenFilter(TokenStream input, string sideLabel, int minGram, int maxGram) : this(input, Side.getSide(sideLabel), minGram, maxGram) { } public override bool IncrementToken() { while (true) { if (curTermBuffer == null) { if (!input.IncrementToken()) { return false; } else { curTermBuffer = (char[])termAtt.TermBuffer().Clone(); curTermLength = termAtt.TermLength(); curGramSize = minGram; tokStart = offsetAtt.StartOffset(); } } if (curGramSize <= maxGram) { if (!(curGramSize > curTermLength // if the remaining input is too short, we can't generate any n-grams || curGramSize > maxGram)) { // if we have hit the end of our n-gram size range, quit // grab gramSize chars from front or back int start = side == Side.FRONT ? 0 : curTermLength - curGramSize; int end = start + curGramSize; ClearAttributes(); offsetAtt.SetOffset(tokStart + start, tokStart + end); termAtt.SetTermBuffer(curTermBuffer, start, curGramSize); curGramSize++; return true; } } curTermBuffer = null; } } public override Token Next(Token reusableToken) { return base.Next(reusableToken); } public override Token Next() { return base.Next(); } public override void Reset() { base.Reset(); curTermBuffer = null; } } } 
+4
Jul 11 '12 at 15:05
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