BM25 Java Implementation

BM25 (Best Matching 25) is a ranking function used by search engines to rank matching documents according to their relevance to a given search query.

See also https://en.wikipedia.org/wiki/Okapi_BM25

Simple usage

List<String> corpus = List.of(
      "I love programming",
      "Java is my favorite programming language",
      "I enjoy writing code in Java",
      "Java is another popular programming language",
      "I find programming fascinating",
      "I love Java",
      "I prefer Java over Python"
  );

  BM25 bm25 = new BM25(corpus);

  List<Map.Entry<Integer, Double>> results = bm25.search("I love java");

  for (Map.Entry<Integer, Double> entry : results) {
      System.out.println("Sentence " + entry.getKey() + " : Score = " + entry.getValue() + " - [" + corpus.get(entry.getKey()) + "]");
  }

Sentence 5 : Score = 2.286729869084079 - [I love Java]
Sentence 0 : Score = 1.8387268317084793 - [I love programming]
Sentence 6 : Score = 0.7294916714788526 - [I prefer Java over Python]
Sentence 2 : Score = 0.6674701123652661 - [I enjoy writing code in Java]
Sentence 4 : Score = 0.40211004330297734 - [I find programming fascinating]
Sentence 1 : Score = 0.33373505618263305 - [Java is my favorite programming language]
Sentence 3 : Score = 0.33373505618263305 - [Java is another popular programming language]

bm25.search("programming");

Sentence 0 : Score = 0.687935390645563 - [I love programming]
Sentence 4 : Score = 0.6174639603843102 - [I find programming fascinating]
Sentence 1 : Score = 0.5124700885780712 - [Java is my favorite programming language]
Sentence 3 : Score = 0.5124700885780712 - [Java is another popular programming language]
Sentence 2 : Score = 0.0 - [I enjoy writing code in Java]
Sentence 5 : Score = 0.0 - [I love Java]
Sentence 6 : Score = 0.0 - [I prefer Java over Python]

With stop words

Get better results by removing language-specific stop words.

Based on ISO provided list from https://github.com/stopwords-iso

Current implementation supports English, French, German, Dutch, Italian and Spanish stop words.

      BM25 bm25 = new BM25(corpus, StopWords.ENGLISH);

With Stemming

Get better results by using stemming.

Stemming maps different forms of the same word to a common "stem". For example, the English stemmer maps running, run, runs to run. So a search for 'running' would also find documents which only have the other forms.

      BM25 bm25 = new BM25(corpus, StopWords.ENGLISH, new EnglishStemmer());

The default implementation uses the Porter2 stemmer from Snowball.
You can add other Stemmer implementations, for example, CoreNLP or Lucene.