[chains] Adding methods for determining if a venue name is a known chain, generating an alternate form (plurals, other spellings) for queries

This commit is contained in:
Al
2016-05-20 13:25:42 -04:00
parent 669f2c2e52
commit 319e4649cf

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import random
from geodata.addresses.config import address_config
from geodata.address_expansions.gazetteers import chains_gazetteer
from geodata.categories.query import *
from geodata.text.normalize import normalized_tokens
from geodata.text.tokenize import tokenize, token_types
class Chain(object):
@classmethod
def tokenize_name(cls, name):
if not name:
return []
tokens = normalized_tokens(name)
return tokens
@classmethod
def possible_chain(cls, name):
'''
Determines if a venue name contains the name of a known chain store.
Returns a tuple of:
(True/False, known chain phrases, other tokens)
Handles cases like "Hard Rock Cafe Times Square" and allows for downstream
decision making (i.e. if the tokens have a low IDF in the local area we might
want to consider it a chain).
'''
tokens = cls.tokenize_name(name)
if not tokens:
return False
matches = chains_gazetteer.filter(tokens)
other_tokens = []
phrases = []
for t, c, l, d in matches:
if c == token_types.PHRASE:
phrases.append((t, c, l, d))
else:
other_tokens.append((t, c))
return len(phrases) > 0, phrases, other_tokens if len(phrases) > 0 else []
@classmethod
def extract(cls, name):
'''
Determines if an entire venue name matches a known chain store.
Note: to avoid false positives, only return True if all of the tokens
in the venue's name are part of a single chain store phrase. This will
miss a few things like "Hard Rock Cafe Times Square" and the like.
It will however handle compound chain stores like Subway/Taco Bell
'''
possible, phrases, other_tokens = cls.possible_chain(name)
is_chain = possible and not any((c in token_types.WORD_TOKEN_TYPES for t, c in other_tokens))
return is_chain, phrases if is_chain else []
@classmethod
def alternate_form(cls, language, dictionary, canonical):
choices = address_config.sample_phrases.get((language, dictionary), {}).get(canonical)
if not choices:
return canonical
return random.choice(choices)