textrank.py
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# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from ..sim.bm25 import BM25
class TextRank(object):
def __init__(self, docs):
self.docs = docs
self.bm25 = BM25(docs)
self.D = len(docs)
self.d = 0.85
self.weight = []
self.weight_sum = []
self.vertex = []
self.max_iter = 200
self.min_diff = 0.001
self.top = []
def solve(self):
for cnt, doc in enumerate(self.docs):
scores = self.bm25.simall(doc)
self.weight.append(scores)
self.weight_sum.append(sum(scores)-scores[cnt])
self.vertex.append(1.0)
for _ in range(self.max_iter):
m = []
max_diff = 0
for i in range(self.D):
m.append(1-self.d)
for j in range(self.D):
if j == i or self.weight_sum[j] == 0:
continue
m[-1] += (self.d*self.weight[j][i]
/ self.weight_sum[j]*self.vertex[j])
if abs(m[-1] - self.vertex[i]) > max_diff:
max_diff = abs(m[-1] - self.vertex[i])
self.vertex = m
if max_diff <= self.min_diff:
break
self.top = list(enumerate(self.vertex))
self.top = sorted(self.top, key=lambda x: x[1], reverse=True)
def top_index(self, limit):
return list(map(lambda x: x[0], self.top))[:limit]
def top(self, limit):
return list(map(lambda x: self.docs[x[0]], self.top))
class KeywordTextRank(object):
def __init__(self, docs):
self.docs = docs
self.words = {}
self.vertex = {}
self.d = 0.85
self.max_iter = 200
self.min_diff = 0.001
self.top = []
def solve(self):
for doc in self.docs:
que = []
for word in doc:
if word not in self.words:
self.words[word] = set()
self.vertex[word] = 1.0
que.append(word)
if len(que) > 5:
que.pop(0)
for w1 in que:
for w2 in que:
if w1 == w2:
continue
self.words[w1].add(w2)
self.words[w2].add(w1)
for _ in range(self.max_iter):
m = {}
max_diff = 0
tmp = filter(lambda x: len(self.words[x[0]]) > 0,
self.vertex.items())
tmp = sorted(tmp, key=lambda x: x[1] / len(self.words[x[0]]))
for k, v in tmp:
for j in self.words[k]:
if k == j:
continue
if j not in m:
m[j] = 1 - self.d
m[j] += (self.d / len(self.words[k]) * self.vertex[k])
for k in self.vertex:
if k in m and k in self.vertex:
if abs(m[k] - self.vertex[k]) > max_diff:
max_diff = abs(m[k] - self.vertex[k])
self.vertex = m
if max_diff <= self.min_diff:
break
self.top = list(self.vertex.items())
self.top = sorted(self.top, key=lambda x: x[1], reverse=True)
def top_index(self, limit):
return list(map(lambda x: x[0], self.top))[:limit]
def top(self, limit):
return list(map(lambda x: self.docs[x[0]], self.top))