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I am doing stemming using Porter and Lancaster and I find these observations:

Input: replied
Porter: repli
Lancaster: reply


Input:  twice
porter:  twice
lancaster:  twic

Input:  came
porter:  came
lancaster:  cam

Input:  In
porter:  In
lancaster:  in

My question are:

  • Lancaster was supposed to be "aggressive" stemmer but it worked properly with replied. Why?
  • The word In remained the same in Porter with uppercase In, Why?
  • Notice that the Lancaster is removing words ending with e, Why?

I am not able to understand these concepts. Could you please help?

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1 回答 1

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问:Lancaster 应该是“激进的”词干提取器,但它与replied. 为什么?

这是因为在https://github.com/nltk/nltk/pull/1654中改进了 Lancaster 词干分析器的实现

如果我们看一下https://github.com/nltk/nltk/blob/develop/nltk/stem/lancaster.py#L62,有一个后缀规则,要更改-ied > -y

default_rule_tuple = (
    "ai*2.",   # -ia > -   if intact
    "a*1.",    # -a > -    if intact
    "bb1.",    # -bb > -b
    "city3s.", # -ytic > -ys
    "ci2>",    # -ic > -
    "cn1t>",   # -nc > -nt
    "dd1.",    # -dd > -d
    "dei3y>",  # -ied > -y
    ...)

该功能允许用户输入新规则,如果没有添加其他规则,那么它将使用将应用self.default_rule_tupleparseRules地方https://github.com/nltk/nltk/blob/develop/nltk/stem/lancaster。 py#L196rule_tuple

def parseRules(self, rule_tuple=None):
    """Validate the set of rules used in this stemmer.
    If this function is called as an individual method, without using stem
    method, rule_tuple argument will be compiled into self.rule_dictionary.
    If this function is called within stem, self._rule_tuple will be used.
    """
    # If there is no argument for the function, use class' own rule tuple.
    rule_tuple = rule_tuple if rule_tuple else self._rule_tuple
    valid_rule = re.compile("^[a-z]+\*?\d[a-z]*[>\.]?$")
    # Empty any old rules from the rule set before adding new ones
    self.rule_dictionary = {}

    for rule in rule_tuple:
        if not valid_rule.match(rule):
            raise ValueError("The rule {0} is invalid".format(rule))
        first_letter = rule[0:1]
        if first_letter in self.rule_dictionary:
            self.rule_dictionary[first_letter].append(rule)
        else:
            self.rule_dictionary[first_letter] = [rule]

default_rule_tuple实际上来自paice-husk 词干分析器的嗖嗖实现,也就是 Lancaster 词干分析器https://github.com/nltk/nltk/pull/1661 =)

问:在 Porter 中,In 还是大写的 In,为什么?

这超级有趣!而且很可能是一个错误。

>>> from nltk.stem import PorterStemmer
>>> porter = PorterStemmer()
>>> porter.stem('In')
'In'

如果我们查看代码,首先将PorterStemmer.stem()其变为小写,https://github.com/nltk/nltk/blob/develop/nltk/stem/porter.py#L651

def stem(self, word):
    stem = word.lower()

    if self.mode == self.NLTK_EXTENSIONS and word in self.pool:
        return self.pool[word]

    if self.mode != self.ORIGINAL_ALGORITHM and len(word) <= 2:
        # With this line, strings of length 1 or 2 don't go through
        # the stemming process, although no mention is made of this
        # in the published algorithm.
        return word

    stem = self._step1a(stem)
    stem = self._step1b(stem)
    stem = self._step1c(stem)
    stem = self._step2(stem)
    stem = self._step3(stem)
    stem = self._step4(stem)
    stem = self._step5a(stem)
    stem = self._step5b(stem)

    return stem

但是如果我们查看代码,其他所有内容都返回stem小写的 ,但是有两个 if 子句返回某种形式的原始word未小写!

if self.mode == self.NLTK_EXTENSIONS and word in self.pool:
    return self.pool[word]

if self.mode != self.ORIGINAL_ALGORITHM and len(word) <= 2:
    # With this line, strings of length 1 or 2 don't go through
    # the stemming process, although no mention is made of this
    # in the published algorithm.
    return word

第一个 if 子句检查单词是否在self.pool包含不规则单词及其词干的内部。

第二个检查是否len(word)<= 2,然后返回它的原始形式,在“In”的情况下,第二个 if 子句返回 True,因此返回原始的非小写形式。

问:请注意,Lancaster 正在删除以“来”结尾的单词e,为什么?

毫不奇怪也来自default_rule_tuple https://github.com/nltk/nltk/blob/develop/nltk/stem/lancaster.py#L67,有一条规则会改变-e > -=)

问:如何禁用-e > -规则default_rule_tuple

(Un-)幸运的是,该LancasterStemmer._rule_tuple对象是一个不可变的元组,所以我们不能简单地从中删除一个项目,但我们可以覆盖它 =)

>>> from nltk.stem import LancasterStemmer
>>> lancaster = LancasterStemmer()
>>> lancaster.stem('came')
'cam'

# Create a new stemmer object to refresh the cache.
>>> lancaster = LancasterStemmer()
>>> temp_rule_list = list(lancaster._rule_tuple)
# Find the 'e1>' rule.
>>> lancaster._rule_tuple.index('e1>') 
12

# Create a temporary rule list from the tuple.
>>> temp_rule_list = list(lancaster._rule_tuple)
# Remove the rule.
>>> temp_rule_list.pop(12)
'e1>'
# Override the `._rule_tuple` variable.
>>> lancaster._rule_tuple = tuple(temp_rule_list)

# Et voila!
>>> lancaster.stem('came')
'came'
于 2020-02-25T05:25:50.093 回答