ユークリッド距離

def sim_distance(prefs, person1, preson2)
	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){|result, item|
		result + (prefs[person1][item]-prefs[person2][item])**2
	}
	return 1/(1+sum_of_squares)
end

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

ピアソン相関係数

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

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

類似度

def top_matches(prefs, person, n=5, similarity=:sim_pearson)
	scores = Array.new
	prefs.each do |key,value|
		if key != person
			scores << [__send__(similarity, prefs, person, key),key]
		end
	end
	scores.sort.reverse[0,n]
end

p top_matches(critics_ja, 'xxx')

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

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

	rankings = Array.new
	totals_h.each do |item,total|
		rankings << [total/sim_sums_h[item], item]
	end
	rankings.sort.reverse
end

p get_recommendations(critics_ja, 'xxx')

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

menu = transform_prefs(ciritics_ja)
p top_matches(menu, 'xxx')