def iterTerms(n, text, emmit_head_tail=False):
'''Iterate n-gram terms in given text and return a generator.
All English in
terms will be lower case. All first and last terms in a sentence will be
emitted another term in the result with 'B' and 'E' prefix.
For example:
'C1C2C3'
in uni-gram term will be emitted as
['C1', 'BC1', 'C2', 'C3', 'EC3']
where the C1, C2 and C3 are Chinese words.
'''
for sentence in splitSentence(text):
first = True
term = None
for term in util.ngram(n, sentence):
term = term.lower()
yield term
if first:
if emmit_head_tail:
yield 'B' + term
first = False
if term is not None:
if emmit_head_tail:
yield 'E' + term
def iterTerms(n, text, emmit_head_tail=False):
"""Iterate n-gram terms in given text and return a generator.
All English in
terms will be lower case. All first and last terms in a sentence will be
emitted another term in the result with 'B' and 'E' prefix.
For example:
'C1C2C3'
in uni-gram term will be emitted as
['C1', 'BC1', 'C2', 'C3', 'EC3']
where the C1, C2 and C3 are Chinese words.
"""
for sentence in splitSentence(text):
first = True
term = None
for term in util.ngram(n, sentence):
term = term.lower()
yield term
if first:
if emmit_head_tail:
yield 'B' + term
first = False
if term is not None:
if emmit_head_tail:
yield 'E' + term
def splitTerms(self, text, categories=None):
'''Split text into terms, categories is a list of category to read
lexicon data from, if it is empty, it means to get data from all
categories
'''
all_category = self.getCategoryList()
if not categories:
categories = all_category
c_list = []
for name in categories:
c = self.getCategory(name)
if not c:
self.logger.error('Category %s not exist', name)
continue
c_list.append(c)
grams = []
for n in range(1, self.ngram + 1):
terms = []
for term in util.ngram(n, text):
score = self._getTermScore(term, n, c_list)
self.logger.debug('Term=%s, Score=%s', term, score)
terms.append((term, score))
grams.append(terms)
terms, best_score = findBestSegment(grams)
self.logger.debug('Best score: %s', best_score)
return terms
def splitTerms(self, text, categories=None):
"""Split text into terms, categories is a list of category to read
lexicon data from, if it is empty, it means to get data from all
categories
"""
all_category = self.getCategoryList()
if not categories:
categories = all_category
c_list = []
for name in categories:
c = self.getCategory(name)
if not c:
self.logger.error('Category %s not exist', name)
continue
c_list.append(c)
grams = []
for n in xrange(1, self.ngram+1):
terms = []
for term in util.ngram(n, text):
score = self._getTermScore(term, n, c_list)
self.logger.debug('Term=%s, Score=%s', term, score)
terms.append((term, score))
grams.append(terms)
terms, best_score = findBestSegment(grams)
self.logger.debug('Best score: %s', best_score)
return terms