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similarity.py
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from nltk.corpus import wordnet as wn
class similarityHousehold():
def Remove(self, duplicate):
final = []
for num in duplicate:
if num not in final:
final.append(num)
return final
def hasNumbers(self, inputString):
return any(char.isdigit() for char in inputString)
def __init__(self, entities, properties, perceived, weights):
self.entities = entities
self.properties = properties
self.perceived = perceived
self.weights = weights
def cleaning_entities(self):
property_list = self.Remove(self.properties)
list1 = []
entity_property = {}
for i in range(len(self.entities)):
first_cleaning = self.entities[i].replace('/a/[', '').replace(']', '')
for j in range(len(self.properties)):
if self.properties[j] + '/' in first_cleaning:
second_cleaning = first_cleaning.replace(self.properties[j] + '/', '').replace(',', '')
if entity_property.get(self.properties[j]) == None:
entity_property.setdefault(self.properties[j], []).append(second_cleaning)
else:
entity_property[self.properties[j]].append(second_cleaning)
break
list1.append((second_cleaning, self.weights[i]))
list_properties = ['/r/RelatedTo', '/r/AtLocation', '/r/UsedFor', '/r/IsA']
new_hash_entity_property = {}
for property in entity_property:
if property in list_properties:
new_hash_entity_property[property] = entity_property[property]
return list1, new_hash_entity_property
def cleaning_entities_second(self, entities_observed, perceived_weights):
for observed in entities_observed:
for entity in range(len(entities_observed[observed])-1, -1, -1):
if not (entities_observed[observed][entity].count("/en/") == 2):
del entities_observed[observed][entity]
else:
for perceived_entity in self.perceived:
if (('/c/en/' + perceived_entity + '/') in entities_observed[observed][entity]):
entities_observed[observed][entity] = entities_observed[observed][entity].replace('/c/en/' + perceived_entity + '/', '')
if (('/c/en' + perceived_entity + '/n/') in entities_observed[observed][entity]):
entities_observed[observed][entity] = entities_observed[observed][entity].replace('/c/en/' + perceived_entity + '/n/', '')
for observed in entities_observed:
annotator = 0
for i in entities_observed[observed]:
if ('wn/' in i):
entities_observed[observed][annotator] = entities_observed[observed][annotator].replace('wn/', '_')
if ('/n/' in i):
entities_observed[observed][annotator] = entities_observed[observed][annotator].replace('/n/', '')
if ('/v/' in i):
entities_observed[observed][annotator] = entities_observed[observed][annotator].replace('/v/', '')
if ('/a/' in i):
entities_observed[observed][annotator] = entities_observed[observed][annotator].replace('/a/', '')
if ('/c/en/' in i):
entities_observed[observed][annotator] = entities_observed[observed][annotator].replace('/c/en/', '')
if ('n/' in i):
entities_observed[observed][annotator] = entities_observed[observed][annotator].replace('n/', '')
if ('/' in i):
entities_observed[observed][annotator] = entities_observed[observed][annotator].replace('/', '')
annotator += 1
for observed in entities_observed:
entities_observed[observed] = self.Remove(entities_observed[observed])
for i in entities_observed[observed]:
if self.hasNumbers(i) == True:
entities_observed[observed].remove(i)
helper_list_weights = []
for property in entities_observed:
for entity in entities_observed[property]:
helper_list_weights.append(entity)
list_with_weights = []
for entity in helper_list_weights:
for weight in perceived_weights:
if entity in weight[0]:
list_with_weights.append((entity, weight[1]))
return entities_observed, list_with_weights
def grounding(self, cleaned_entities, weigths_of_entities):
listWordNet = ['.n.01', '.v.01', '.a.01', '.r.01']
for observed in cleaned_entities:
for i in range(len(cleaned_entities[observed])-1, -1, -1):
wordNet = wn.synsets(cleaned_entities[observed][i])
if wordNet != []:
wordnet_entity = wordNet[0].name()
for j in listWordNet:
if j in wordnet_entity:
cleaned_entities[observed][i] = wordnet_entity.replace(j, '')
break
else:
del cleaned_entities[observed][i]
helper_list_weight = []
for property in cleaned_entities:
for entity in cleaned_entities[property]:
helper_list_weight.append(entity)
helper_weight_final = []
for weight in weigths_of_entities:
for helper in helper_list_weight:
if helper in weight[0]:
helper_weight_final.append((helper, weight[1]))
visited = set()
weight_final = []
for entity1, emtity2 in helper_weight_final:
if not entity1 in visited:
visited.add(entity1)
weight_final.append((entity1, emtity2))
return cleaned_entities, weight_final
def strong_related(self, cleaned_final, weight_final):
weight_final = sorted(weight_final, key=lambda x: x[1], reverse=True)
new_cleaned_hash = {}
if len(weight_final) > 10:
weight_final = set(weight_final[:10])
for property in cleaned_final:
cleaned_final[property] = self.Remove(cleaned_final[property])
for property in cleaned_final:
for entity in cleaned_final[property]:
for strong_entity in weight_final:
if strong_entity[0] == entity:
if new_cleaned_hash.get(property) == None:
new_cleaned_hash.setdefault(property, []).append(entity)
else:
new_cleaned_hash[property].append(entity)
else:
for property in cleaned_final:
new_cleaned_hash[property] = self.Remove(cleaned_final[property])
help = []
for property in new_cleaned_hash:
for entity in new_cleaned_hash[property]:
help.append((entity, property))
visited = set()
output = []
for a, b in help:
if not a in visited:
visited.add(a)
output.append((a, b))
new_cleaned_hash = {}
for tup in output:
if new_cleaned_hash.get(tup[1]) == None:
new_cleaned_hash.setdefault(tup[1], []).append(tup[0])
else:
new_cleaned_hash[tup[1]].append(tup[0])
return new_cleaned_hash, weight_final