场景：
1.计算SimHash值，及Hamming距离。
2.SimHash适用于较长文本（大于三五百字）的相似性比较，文本越短误判率越高。
Python实现：
代码如下
# -*- encoding:utf-8 -*-
import math
import jieba
import jieba.analyse
class SimHash(object):
def getBinStr(self, source):
if source == "":
return 0
else:
x = ord(source[0]) << 7
m = 1000003
mask = 2 ** 128 - 1
for c in source:
x = ((x * m) ^ ord(c)) & mask
x ^= len(source)
if x == -1:
x = -2
x = bin(x).replace('0b', '').zfill(64)[-64:]
return str(x)
def getWeight(self, source):
return ord(source)
def unwrap_weight(self, arr):
ret = ""
for item in arr:
tmp = 0
if int(item) > 0:
tmp = 1
ret += str(tmp)
return ret
def sim_hash(self, rawstr):
seg = jieba.cut(rawstr)
keywords = jieba.analyse.extract_tags("|".join(seg), topK=100, withWeight=True)
ret = []
for keyword, weight in keywords:
binstr = self.getBinStr(keyword)
keylist = []
for c in binstr:
weight = math.ceil(weight)
if c == "1":
keylist.append(int(weight))
else:
keylist.append(-int(weight))
ret.append(keylist)
# 降维
rows = len(ret)
cols = len(ret[0])
result = []
for i in range(cols):
tmp = 0
for j in range(rows):
tmp += int(ret[j][i])
if tmp > 0:
tmp = "1"
elif tmp <= 0:
tmp = "0"
result.append(tmp)
return "".join(result)
def distince(self, hashstr1, hashstr2):
length = 0
for index, char in enumerate(hashstr1):
if char == hashstr2[index]:
continue
else:
length += 1
return length
if __name__ == "__main__":
simhash = SimHash()
str1 = '咱哥俩谁跟谁啊'
str2 = '咱们俩谁跟谁啊'
hash1 = simhash.sim_hash(str1)
print(hash1)
hash2 = simhash.sim_hash(str2)
distince = simhash.distince(hash1, hash2)
value = 5
print("simhash", distince, "距离：", value, "是否相似：", distince<=value)
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