NLPWords Normalization+PorterStemmer源码解析
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Words Normalization
目录
Stemming（词干提取）
词干提取是去除单词的前后缀得到词根的过程
caresses -> caress
ponies -> poni
ties -> ti
caress -> caress
cats -> cat
feed -> feed
agreed -> agree
disabled -> disable
Lemmatisation（词形还原）
词形还原是基于词典，将单词的复杂形态转变成最基础的形态
词形还原不是简单地将前后缀去掉，而是会根据词典将单词进行转换。比如「drove」会转换为「drive」
PorterStemmer源码解析
PorterStemmer是基于Stemming的英文分词工具，源码如下：
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Author : linjie
#!/usr/bin/env python
'''
基于Stemming（词干提取，去除单词的前后缀得到词根的过程）的words normalization的实现
'''
"""Porter Stemming Algorithm
This is the Porter stemming algorithm, ported to Python from the
version coded up in ANSI C by the author. It may be be regarded
as canonical, in that it follows the algorithm presented in
Porter, 1980, An algorithm for suffix stripping, Program, Vol. 14,
no. 3, pp 130-137,
only differing from it at the points maked --DEPARTURE-- below.
See also http://www.tartarus.org/~martin/PorterStemmer
The algorithm as described in the paper could be exactly replicated
by adjusting the points of DEPARTURE, but this is barely necessary,
because (a) the points of DEPARTURE are definitely improvements, and
(b) no encoding of the Porter stemmer I have seen is anything like
as exact as this version, even with the points of DEPARTURE!
Vivake Gupta (v@nano.com)
Release 1: January 2001
Further adjustments by Santiago Bruno (bananabruno@gmail.com)
to allow word input not restricted to one word per line, leading
to:
release 2: July 2008
"""
import sys
class PorterStemmer:
def __init__(self):
"""The main part of the stemming algorithm starts here.
b is a buffer holding a word to be stemmed. The letters are in b[k0],
b[k0+1] ... ending at b[k]. In fact k0 = 0 in this demo program. k is
readjusted downwards as the stemming progresses. Zero termination is
not in fact used in the algorithm.
Note that only lower case sequences are stemmed. Forcing to lower case
should be done before stem(...) is called.
"""
self.b = "" # buffer for word to be stemmed
self.k = 0
self.k0 = 0
self.j = 0 # j is a general offset into the string
def cons(self, i):
"""cons(i) is TRUE <=> b[i] is a consonant."""
if self.b[i] == 'a' or self.b[i] == 'e' or self.b[i] == 'i' or self.b[i] == 'o' or self.b[i] == 'u':
return 0
if self.b[i] == 'y':
if i == self.k0:
return 1
else:
return (not self.cons(i - 1))
return 1
def m(self):
"""m() measures the number of consonant sequences between k0 and j.
if c is a consonant sequence and v a vowel sequence, and <..>
indicates arbitrary presence,
<c><v> gives 0
<c>vc<v> gives 1
<c>vcvc<v> gives 2
<c>vcvcvc<v> gives 3
....
"""
n = 0
i = self.k0
while 1:
if i > self.j:
return n
if not self.cons(i):
break
i = i + 1
i = i + 1
while 1:
while 1:
if i > self.j:
return n
if self.cons(i):
break
i = i + 1
i = i + 1
n = n + 1
while 1:
if i > self.j:
return n
if not self.cons(i):
break
i = i + 1
i = i + 1
def vowelinstem(self):
"""vowelinstem() is TRUE <=> k0,...j contains a vowel"""
for i in range(self.k0, self.j + 1):
if not self.cons(i):
return 1
return 0
def doublec(self, j):
"""doublec(j) is TRUE <=> j,(j-1) contain a double consonant."""
if j < (self.k0 + 1):
return 0
if (self.b[j] != self.b[j-1]):
return 0
return self.cons(j)
def cvc(self, i):
"""cvc(i) is TRUE <=> i-2,i-1,i has the form consonant - vowel - consonant
and also if the second c is not w,x or y. this is used when trying to
restore an e at the end of a short e.g.
cav(e), lov(e), hop(e), crim(e), but
snow, box, tray.
"""
if i < (self.k0 + 2) or not self.cons(i) or self.cons(i-1) or not self.cons(i-2):
return 0
ch = self.b[i]
if ch == 'w' or ch == 'x' or ch == 'y':
return 0
return 1
def ends(self, s):
"""ends(s) is TRUE <=> k0,...k ends with the string s."""
length = len(s)
if s[length - 1] != self.b[self.k]: # tiny speed-up
return 0
if length > (self.k - self.k0 + 1):
return 0
if self.b[self.k-length+1:self.k+1] != s:
return 0
self.j = self.k - length
return 1
def setto(self, s):
"""setto(s) sets (j+1),...k to the characters in the string s, readjusting k."""
length = len(s)
self.b = self.b[:self.j+1] + s + self.b[self.j+length+1:]
self.k = self.j + length
def r(self, s):
"""r(s) is used further down."""
if self.m() > 0:
self.setto(s)
def step1ab(self):
"""step1ab() gets rid of plurals and -ed or -ing. e.g.
caresses -> caress
ponies -> poni
ties -> ti
caress -> caress
cats -> cat
feed -> feed
agreed -> agree
disabled -> disable
matting -> mat
mating -> mate
meeting -> meet
milling -> mill
messing -> mess
meetings -> meet
"""
if self.b[self.k] == 's':
if self.ends("sses"):
self.k = self.k - 2
elif self.ends("ies"):
self.setto("i")
elif self.b[self.k - 1] != 's':
self.k = self.k - 1
if self.ends("eed"):
if self.m() > 0:
self.k = self.k - 1
elif (self.ends("ed") or self.ends("ing")) and self.vowelinstem():
self.k = self.j
if self.ends("at"): self.setto("ate")
elif self.ends("bl"): self.setto("ble")
elif self.ends("iz"): self.setto("ize")
elif self.doublec(self.k):
self.k = self.k - 1
ch = self.b[self.k]
if ch == 'l' or ch == 's' or ch == 'z':
self.k = self.k + 1
elif (self.m() == 1 and self.cvc(self.k)):
self.setto("e")
def step1c(self):
"""step1c() turns terminal y to i when there is another vowel in the stem."""
if (self.ends("y") and self.vowelinstem()):
self.b = self.b[:self.k] + 'i' + self.b[self.k+1:]
def step2(self):
"""step2() maps double suffices to single ones.
so -ization ( = -ize plus -ation) maps to -ize etc. note that the
string before the suffix must give m() > 0.
"""
if self.b[self.k - 1] == 'a':
if self.ends("ational"): self.r("ate")
elif self.ends("tional"): self.r("tion")
elif self.b[self.k - 1] == 'c':
if self.ends("enci"): self.r("ence")
elif self.ends("anci"): self.r("ance")
elif self.b[self.k - 1] == 'e':
if self.ends("izer"): self.r("ize")
elif self.b[self.k - 1] == 'l':
if self.ends("bli"): self.r("ble") # --DEPARTURE--
# To match the published algorithm, replace this phrase with
# if self.ends("abli"): self.r("able")
elif self.ends("alli"): self.r("al")
elif self.ends("entli"): self.r("ent")
elif self.ends("eli"): self.r("e")
elif self.ends("ousli"): self.r("ous")
elif self.b[self.k - 1] == 'o':
if self.ends("ization"): self.r("ize")
elif self.ends("ation"): self.r("ate")
elif self.ends("ator"): self.r("ate")
elif self.b[self.k - 1] == 's':
if self.ends("alism"): self.r("al")
elif self.ends("iveness"): self.r("ive")
elif self.ends("fulness"): self.r("ful")
elif self.ends("ousness"): self.r("ous")
elif self.b[self.k - 1] == 't':
if self.ends("aliti"): self.r("al")
elif self.ends("iviti"): self.r("ive")
elif self.ends("biliti"): self.r("ble")
elif self.b[self.k - 1] == 'g': # --DEPARTURE--
if self.ends("logi"): self.r("log")
# To match the published algorithm, delete this phrase
def step3(self):
"""step3() dels with -ic-, -full, -ness etc. similar strategy to step2."""
if self.b[self.k] == 'e':
if self.ends("icate"): self.r("ic")
elif self.ends("ative"): self.r("")
elif self.ends("alize"): self.r("al")
elif self.b[self.k] == 'i':
if self.ends("iciti"): self.r("ic")
elif self.b[self.k] == 'l':
if self.ends("ical"): self.r("ic")
elif self.ends("ful"): self.r("")
elif self.b[self.k] == 's':
if self.ends("ness"): self.r("")
def step4(self):
"""step4() takes off -ant, -ence etc., in context <c>vcvc<v>."""
if self.b[self.k - 1] == 'a':
if self.ends("al"): pass
else: return
elif self.b[self.k - 1] == 'c':
if self.ends("ance"): pass
elif self.ends("ence"): pass
else: return
elif self.b[self.k - 1] == 'e':
if self.ends("er"): pass
else: return
elif self.b[self.k - 1] == 'i':
if self.ends("ic"): pass
else: return
elif self.b[self.k - 1] == 'l':
if self.ends("able"): pass
elif self.ends("ible"): pass
else: return
elif self.b[self.k - 1] == 'n':
if self.ends("ant"): pass
elif self.ends("ement"): pass
elif self.ends("ment"): pass
elif self.ends("ent"): pass
else: return
elif self.b[self.k - 1] == 'o':
if self.ends("ion") and (self.b[self.j] == 's' or self.b[self.j] == 't'): pass
elif self.ends("ou"): pass
# takes care of -ous
else: return
elif self.b[self.k - 1] == 's':
if self.ends("ism"): pass
else: return
elif self.b[self.k - 1] == 't':
if self.ends("ate"): pass
elif self.ends("iti"): pass
else: return
elif self.b[self.k - 1] == 'u':
if self.ends("ous"): pass
else: return
elif self.b[self.k - 1] == 'v':
if self.ends("ive"): pass
else: return
elif self.b[self.k - 1] == 'z':
if self.ends("ize"): pass
else: return
else:
return
if self.m() > 1:
self.k = self.j
def step5以上是关于NLPWords Normalization+PorterStemmer源码解析的主要内容，如果未能解决你的问题，请参考以下文章
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