29

I'm processing some English texts in a Java application, and I need to stem them. For example, from the text "amenities/amenity" I need to get "amenit".

The function looks like:

String stemTerm(String term){
   ...
}

I've found the Lucene Analyzer, but it looks way too complicated for what I need. http://lucene.apache.org/java/2_2_0/api/org/apache/lucene/analysis/PorterStemFilter.html

Is there a way to use it to stem words without building an Analyzer? I don't understand all the Analyzer business...

EDIT: I actually need a stemming + lemmatization. Can Lucene do this?

rae1
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Mulone
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    Why do you need to stem the words yourself? Lucene has an analyzer called SnowballAnalyzer which you just instantiate with the stemmer name, e.g. `new SnowballAnalyzer("English");`. – Thomas Mar 22 '11 at 13:22
  • Knuth-Pratt Algorithm Implementation http://www.fmi.uni-sofia.bg/fmi/logic/vboutchkova/sources/KMPMatch_java.html – Dead Programmer Mar 22 '11 at 13:26

7 Answers7

29

SnowballAnalyzer is deprecated, you can use Lucene Porter Stemmer instead:

 PorterStemmer stem = new PorterStemmer();
 stem.setCurrent(word);
 stem.stem();
 String result = stem.getCurrent();

Hope this help!

arbc
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    PorterStemmer no longer public (stupidly) - see also http://stackoverflow.com/questions/15422485/lucene-porter-stemmer-not-public – 8bitjunkie Jun 11 '13 at 15:00
23
import org.apache.lucene.analysis.PorterStemmer;
...
String stemTerm (String term) {
    PorterStemmer stemmer = new PorterStemmer();
    return stemmer.stem(term);
}

See here for more details. If stemming is all you want to do, then you should use this instead of Lucene.

Edit: You should lowercase term before passing it to stem().

nikhil500
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    Is it possible to combine the filter for stop words with the stemmer? – Mulone Mar 23 '11 at 12:22
  • Do you want to filter stop words from a string with multiple words or have you already tokenised (separated) the words and want to check just a single word? If its just a single term like above, then just create a `Set` of all stop words and do a `.contains()`. – nikhil500 Mar 23 '11 at 15:26
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    As of the current version of Lucene (3.5), PorterStemmer, although it exists, is not public. I'm not sure who/what uses it, but we can't. – Rob Cranfill Jan 19 '12 at 20:02
  • PorterStemmer no longer public (stupidly) - see also http://stackoverflow.com/questions/15422485/lucene-porter-stemmer-not-public – 8bitjunkie Jun 11 '13 at 14:59
6

Why aren't you using the "EnglishAnalyzer"? It's simple to use it and I think it'd solve your problem:

EnglishAnalyzer en_an = new EnglishAnalyzer(Version.LUCENE_34);
QueryParser parser = new QueryParser(Version.LUCENE_34, "your_field", en_an);
String str = "amenities";
System.out.println("result: " + parser.parse(str)); //amenit

Hope it helps you!

Max
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5

The previous example applies stemming to a search query, so if you are interesting to stem a full text you can try the following:

import java.io.*;
import org.apache.lucene.analysis.*;
import org.apache.lucene.analysis.tokenattributes.*;
import org.apache.lucene.analysis.snowball.*;
import org.apache.lucene.util.*;
...
public class Stemmer{
    public static String Stem(String text, String language){
        StringBuffer result = new StringBuffer();
        if (text!=null && text.trim().length()>0){
            StringReader tReader = new StringReader(text);
            Analyzer analyzer = new SnowballAnalyzer(Version.LUCENE_35,language);
            TokenStream tStream = analyzer.tokenStream("contents", tReader);
            TermAttribute term = tStream.addAttribute(TermAttribute.class);

            try {
                while (tStream.incrementToken()){
                    result.append(term.term());
                    result.append(" ");
                }
            } catch (IOException ioe){
                System.out.println("Error: "+ioe.getMessage());
            }
        }

        // If, for some reason, the stemming did not happen, return the original text
        if (result.length()==0)
            result.append(text);
        return result.toString().trim();
    }

    public static void main (String[] args){
        Stemmer.Stem("Michele Bachmann amenities pressed her allegations that the former head of her Iowa presidential bid was bribed by the campaign of rival Ron Paul to endorse him, even as one of her own aides denied the charge.", "English");
    }
}

The TermAttribute class has been deprecated and will not longer be supported in Lucene 4, but the documentation is not clear on what to use at its place.

Also in the first example the PorterStemmer is not available as a class (hidden) so you cannot use it directly.

Hope this helps.

  • Giancarlo's Answer is correct with a minor change of TermAttribute to CharTermAttribute as TermAttribute is deprecated. – amas Jul 24 '12 at 03:02
3

Here is how you can use Snowball Stemmer in JAVA:

import org.tartarus.snowball.ext.EnglishStemmer;

EnglishStemmer english = new EnglishStemmer();
String[] words = tokenizer("bank banker banking");
for(int i = 0; i < words.length; i++){
        english.setCurrent(words[i]);
        english.stem();
        System.out.println(english.getCurrent());
}
UserNeD
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0

Since the PorterStemmer is not public, we ca't call the stem function of PorterStemmer.

Instead we can KStemmer/KStemFilter to stemming the words to its root word.

Below is the scala code snippet which accepts the string and transforms to stemmed string

import org.apache.lucene.analysis.core.WhitespaceTokenizer import org.apache.lucene.analysis.en.KStemFilter

import java.io.StringReader

object Stemmer { def stem(input:String):String={

val stemmed_string = new StringBuilder()

val inputReader = new StringReader(input.toLowerCase)

val whitespaceTokenizer = new WhitespaceTokenizer()
whitespaceTokenizer.setReader(inputReader)

val kStemmedTokenStream = new KStemFilter(whitespaceTokenizer)
import org.apache.lucene.analysis.tokenattributes.CharTermAttribute

val charTermAttribute = kStemmedTokenStream.addAttribute(classOf[CharTermAttribute])

kStemmedTokenStream.reset
while (kStemmedTokenStream.incrementToken) {
  val term = charTermAttribute.toString
  stemmed_string.append(term+" ")
}
stemmed_string.toString().trim.toUpperCase

}

}

Ram Kumar
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Ling pipe provides a number of tokenizers . They can be used for stemming and stop word removal . Its a simple and a effective means of stemming.

CTsiddharth
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