I\'m thinking of putting a stop words in my similarity program and then a stemmer (going for porters 1 or 2 depends on what easiest to implement)
I was wondering that si
Yes, you can wrap any stemmer so that you can write something like
String stemmedString = stemmer.stemAndRemoveStopwords(inputString, stopWordList);
Internally, your stemAndRemoveStopwords would
If you're not implementing this for academic reasons you should consider using the Lucene library. In either case it might be good for reference. It has classes for tokenization, stop word filtering, stemming and similarity. Here's a quick example using Lucene 3.0 to remove stop words and stem an input string:
public static String removeStopWordsAndStem(String input) throws IOException {
Set<String> stopWords = new HashSet<String>();
stopWords.add("a");
stopWords.add("I");
stopWords.add("the");
TokenStream tokenStream = new StandardTokenizer(
Version.LUCENE_30, new StringReader(input));
tokenStream = new StopFilter(true, tokenStream, stopWords);
tokenStream = new PorterStemFilter(tokenStream);
StringBuilder sb = new StringBuilder();
TermAttribute termAttr = tokenStream.getAttribute(TermAttribute.class);
while (tokenStream.incrementToken()) {
if (sb.length() > 0) {
sb.append(" ");
}
sb.append(termAttr.term());
}
return sb.toString();
}
Which if used on your strings like this:
public static void main(String[] args) throws IOException {
String one = "I decided buy something from the shop.";
String two = "Nevertheless I decidedly bought something from a shop.";
System.out.println(removeStopWordsAndStem(one));
System.out.println(removeStopWordsAndStem(two));
}
Yields this output:
decid bui someth from shop
Nevertheless decidedli bought someth from shop
You don't have to deal with the whole text. Just split it, apply your stopword filter and stemming algorithm, then build the string again using a StringBuilder
:
StrinBuilder builder = new StringBuilder(text.length());
String[] words = text.split("\\s+");
for (String word : words) {
if (stopwordFilter.check(word)) { // Apply stopword filter.
word = stemmer.stem(word); // Apply stemming algorithm.
builder.append(word);
}
}
text = builder.toString();