Module: CollaborativeFiltering

Defined in:
lib/collaborative_filtering/version.rb,
lib/collaborative_filtering/collaborative_filtering.rb

Defined Under Namespace

Modules: Sample

Constant Summary collapse

VERSION = 
'0.6.2'

Class Method Summary collapse

Class Method Details

.get_recommendations(prefs, person, similarity = :sim_pearson) ⇒ Object 



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# File 'lib/collaborative_filtering/collaborative_filtering.rb', line 34

def get_recommendations(prefs, person, similarity = :sim_pearson)
  totals_h = Hash.new(0)
  sim_sums_h = Hash.new(0)

  prefs.each_key do |other|
    next if other == person
    sim = __send__(similarity, prefs, person, other)
    next if sim <= 0
    prefs[other].each_key do |item|
      if !prefs[person].keys.include?(item) || prefs[person][item] == 0
        totals_h[item] += prefs[other][item] * sim
        sim_sums_h[item] += sim
      end
    end
  end

  rankings = []
  totals_h.each { |item, total| rankings << [total / sim_sums_h[item], item] }
  rankings.sort.reverse
end

.shared_items_a(prefs, person1, person2) ⇒ Object 



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# File 'lib/collaborative_filtering/collaborative_filtering.rb', line 66

def shared_items_a(prefs, person1, person2)
  prefs[person1].keys & prefs[person2].keys
end

.sim_distance(prefs, person1, person2) ⇒ Object 



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# File 'lib/collaborative_filtering/collaborative_filtering.rb', line 3

def sim_distance(prefs, person1, person2)
  shared_items_a = shared_items_a(prefs, person1, person2)
  return 0 if shared_items_a.size == 0
  sum_of_squares = shared_items_a.inject(0) { |a, e| a + (prefs[person1][e] - prefs[person2][e])**2 }
  1 / (1 + sum_of_squares)
end

.sim_pearson(prefs, person1, person2) ⇒ Object 



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# File 'lib/collaborative_filtering/collaborative_filtering.rb', line 10

def sim_pearson(prefs, person1, person2)
  shared_items_a = shared_items_a(prefs, person1, person2)

  n = shared_items_a.size
  return 0 if n == 0

  sum1 = shared_items_a.inject(0) { |a, e| a + prefs[person1][e] }
  sum2 = shared_items_a.inject(0) { |a, e| a + prefs[person2][e] }
  sum1_sq = shared_items_a.inject(0) { |a, e| a + prefs[person1][e]**2 }
  sum2_sq = shared_items_a.inject(0) { |a, e| a + prefs[person2][e]**2 }
  sum_products = shared_items_a.inject(0) { |a, e| a + prefs[person1][e] * prefs[person2][e] }

  num = sum_products - (sum1 * sum2 / n)
  den = Math.sqrt((sum1_sq - sum1**2 / n) * (sum2_sq - sum2**2 / n))
  return 0 if den == 0
  num / den
end

.top_matches(prefs, person, n = 5, similarity = :sim_pearson) ⇒ Object 



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# File 'lib/collaborative_filtering/collaborative_filtering.rb', line 28

def top_matches(prefs, person, n = 5, similarity = :sim_pearson)
  scores = []
  prefs.each_key { |k| scores << [__send__(similarity, prefs, person, k), k] if k != person }
  scores.sort.reverse[0, n]
end

.transform_prefs(prefs) ⇒ Object 



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# File 'lib/collaborative_filtering/collaborative_filtering.rb', line 55

def transform_prefs(prefs)
  result = {}
  prefs.each do |person, score_h|
    score_h.each do |item, score|
      result[item] ||= {}
      result[item][person] = score
    end
  end
  result
end