Exemplos de VectorSpaceMapper em Python

Exemplo n.º 1

Arquivo: similarity_metric.py Projeto: shireennagdive/CrossLingualSemanticSimilarity

from tvecs.bilingual_generator import bilingual_generator as bg
from tvecs.vector_space_mapper import vector_space_mapper as vm
from gensim.models import KeyedVectors

import os

train_bilingual_corpus = 'data/bilingual_dictionary/en-fr.txt'
test_bilingual_corpus = 'data/bilingual_dictionary/en-fr.txt'

bilingual_dict = bg.load_bilingual_dictionary(train_bilingual_corpus)

vector_space_mapper = vm.VectorSpaceMapper(
    model_1=KeyedVectors.load_word2vec_format(
        'data/models/t-vex-english-fb-model'),
    model_2=KeyedVectors.load_word2vec_format(
        'data/models/t-vex-french-model')  #change
    ,
    bilingual_dict=bilingual_dict)

vector_space_mapper.map_vector_spaces()

print("Training MSE: {} %".format(
    vector_space_mapper.obtain_mean_square_error_from_dataset(
        dataset_path=train_bilingual_corpus)))

print("Testing MSE: {} %".format(
    vector_space_mapper.obtain_mean_square_error_from_dataset(
        dataset_path=test_bilingual_corpus)))

word1 = raw_input("Please input the english word :")
word2 = raw_input("Please input another english word :")

Exemplo n.º 2

Arquivo: word_synonyms_bengali.py Projeto: shireennagdive/CrossLingualSemanticSimilarity

from tvecs.bilingual_generator import bilingual_generator as bg
from tvecs.vector_space_mapper import vector_space_mapper as vm
from gensim.models import Word2Vec
import os
from gensim.models import KeyedVectors

# train_bilingual_corpus = 'data/bilingual_dictionary/en-fr.txt'
# test_bilingual_corpus = 'data/bilingual_dictionary/en-fr.txt'
#
bilingual_dict = bg.load_bilingual_dictionary(
    'data/bilingual_dictionary/en-bn.txt')

vector_space_mapper = vm.VectorSpaceMapper(
    model_1=Word2Vec.load(os.path.join('data', 'models',
                                       't-vex-english-model')),
    model_2=KeyedVectors.load_word2vec_format(
        'data/models/t-vex-bengali-model'),
    bilingual_dict=bilingual_dict)

vector_space_mapper.map_vector_spaces()

# print("Training MSE: {} %".format(vector_space_mapper.obtain_mean_square_error_from_dataset(
#     dataset_path=train_bilingual_corpus
# )))
#
# print("Testing MSE: {} %".format(vector_space_mapper.obtain_mean_square_error_from_dataset(
#     dataset_path=test_bilingual_corpus
# )))

word = raw_input("Please input the english word :")

Exemplo n.º 3

Arquivo: word_synonyms_hindi.py Projeto: shireennagdive/CrossLingualSemanticSimilarity

from tvecs.bilingual_generator import bilingual_generator as bg
from tvecs.vector_space_mapper import vector_space_mapper as vm
from gensim.models import Word2Vec
import os

# train_bilingual_corpus = 'data/bilingual_dictionary/en-fr.txt'
# test_bilingual_corpus = 'data/bilingual_dictionary/en-fr.txt'
#
bilingual_dict = bg.load_bilingual_dictionary(
    'data/bilingual_dictionary/english_hindi_bd')

vector_space_mapper = vm.VectorSpaceMapper(
    model_1=Word2Vec.load(os.path.join('data', 'models',
                                       't-vex-english-model')),
    model_2=Word2Vec.load(os.path.join('data', 'models', 't-vex-hindi-model')),
    bilingual_dict=bilingual_dict)

vector_space_mapper.map_vector_spaces()

# print("Training MSE: {} %".format(vector_space_mapper.obtain_mean_square_error_from_dataset(
#     dataset_path=train_bilingual_corpus
# )))
#
# print("Testing MSE: {} %".format(vector_space_mapper.obtain_mean_square_error_from_dataset(
#     dataset_path=test_bilingual_corpus
# )))

word = raw_input("Please input the english word :")

while word != '///':
    print vector_space_mapper.get_recommendations_from_word(word.lower(),