Bundler::SimilarityDetector

Constants

SimilarityScore

Public Class Methods

new(corpus) click to toggle source

initialize with an array of words to be matched against

 
 # File bundler/similarity_detector.rb, line 8
def initialize(corpus)
 @corpus = corpus
end

Public Instance Methods

similar_word_list(word, limit = 3) click to toggle source

return the result of 'similar_words', concatenated into a list (eg "a, b, or c")

 
 # File bundler/similarity_detector.rb, line 20
def similar_word_list(word, limit = 3)
 words = similar_words(word, limit)
 if words.length == 1
 words[0]
 elsif words.length > 1
 [words[0..-2].join(", "), words[-1]].join(" or ")
 end
end

similar_words(word, limit = 3) click to toggle source

return an array of words similar to 'word' from the corpus

 
 # File bundler/similarity_detector.rb, line 13
def similar_words(word, limit = 3)
 words_by_similarity = @corpus.map {|w| SimilarityScore.new(w, levenshtein_distance(word, w)) }
 words_by_similarity.select {|s| s.distance <= limit }.sort_by(&:distance).map(&:string)
end

Protected Instance Methods

levenshtein_distance(this, that, ins = 2, del = 2, sub = 1) click to toggle source

www.informit.com/articles/article.aspx?p=683059&seqNum=36

 
 # File bundler/similarity_detector.rb, line 32
def levenshtein_distance(this, that, ins = 2, del = 2, sub = 1)
 # ins, del, sub are weighted costs
 return nil if this.nil?
 return nil if that.nil?
 dm = [] # distance matrix
 # Initialize first row values
 dm[0] = (0..this.length).collect {|i| i * ins }
 fill = [0] * (this.length - 1)
 # Initialize first column values
 (1..that.length).each do |i|
 dm[i] = [i * del, fill.flatten]
 end
 # populate matrix
 (1..that.length).each do |i|
 (1..this.length).each do |j|
 # critical comparison
 dm[i][j] = [
 dm[i - 1][j - 1] + (this[j - 1] == that[i - 1] ? 0 : sub),
 dm[i][j - 1] + ins,
 dm[i - 1][j] + del,
 ].min
 end
 end
 # The last value in matrix is the Levenshtein distance between the strings
 dm[that.length][this.length]
end