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acd_laptops_test.py
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acd_laptops_test.py
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#!/usr/bin/env python
'''
**Aspect Category Detection for the 5th task of SemEval 2016**
Unconstrained Submission for the Laptops domain
Run from the terminal:
>>> python acd_unconstrained_laptops.py --train train.xml --test test.xml
'''
try:
import xml.etree.ElementTree as ET, getopt, logging, sys, random, re, copy, os, warnings
import numpy as np
from collections import Counter
import operator
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.svm import SVC
import nltk
import os
from nltk.stem import PorterStemmer
from xml.sax.saxutils import escape
from sklearn.externals import joblib
import acd_laptops_train
except:
sys.exit('Some package is missing... Perhaps <re>?')
warnings.filterwarnings("ignore") #to ignore sklearns deprecation warnings
# Stopwords, imported from NLTK (v 2.0.4)
stopwords = set(
['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', 'your', 'yours', 'yourself', 'yourselves',
'he', 'him', 'his', 'himself', 'she', 'her', 'hers', 'herself', 'it', 'its', 'itself', 'they', 'them', 'their',
'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', 'these', 'those', 'am', 'is', 'are', 'was',
'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the',
'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against',
'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in',
'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why',
'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only',
'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', 'should', 'now'])
contractions = re.compile(r"'|-|\"")
# all non alphanumeric
symbols = re.compile(r'(\W+)', re.U)
# single character removal
singles = re.compile(r'(\s\S\s)', re.I|re.U)
# separators (any whitespace)
seps = re.compile(r'\s+')
fix = lambda text: escape(text.encode('utf8')).replace('\"', '"')
class AspectCategoryClassifier:
def __init__(self):
self.stemmer = PorterStemmer()
cats = joblib.load('./models/acd/lap/categories.pkl')
self.cat_dict = Counter(cats)
self.w2v_model = joblib.load('./models/acd/lap/w2v_model.pkl')
self.unigrams_lexica = joblib.load('./models/acd/lap/unigrams_lexica.pkl')
self.bigrams_lexica = joblib.load('./models/acd/lap/bigrams_lexica.pkl')
self.bipos_lexica = joblib.load('./models/acd/lap/bipos_lexica.pkl')
self.stemmed_unigrams_lexica = joblib.load('./models/acd/lap/stemmed_unigrams_lexica.pkl')
self.stemmed_bigrams_lexica = joblib.load('./models/acd/lap/stemmed_bigrams_lexica.pkl')
self.idf_dict = joblib.load('./models/acd/lap/idf_dict.pkl')
self.category_centroids = joblib.load('./models/acd/lap/category_centroids.pkl')
self.laptop_clf1 = joblib.load('./models/acd/lap/laptop_clf1Model.pkl')
self.display_clf1 = joblib.load('./models/acd/lap/display_clf1Model.pkl')
self.cpu_clf1 = joblib.load('./models/acd/lap/cpu_clf1Model.pkl')
self.mb_clf1 = joblib.load('./models/acd/lap/mb_clf1Model.pkl')
self.hd_clf1 = joblib.load('./models/acd/lap/hd_clf1Model.pkl')
self.memory_clf1 = joblib.load('./models/acd/lap/memory_clf1Model.pkl')
self.battery_clf1 = joblib.load('./models/acd/lap/battery_clf1Model.pkl')
self.power_clf1 = joblib.load('./models/acd/lap/power_clf1Model.pkl')
self.keyboard_clf1 = joblib.load('./models/acd/lap/keyboard_clf1Model.pkl')
self.mouse_clf1 = joblib.load('./models/acd/lap/mouse_clf1Model.pkl')
self.fans_clf1 = joblib.load('./models/acd/lap/fans_clf1Model.pkl')
self.opt_drives_clf1 = joblib.load('./models/acd/lap/opt_drives_clf1Model.pkl')
self.ports_clf1 = joblib.load('./models/acd/lap/ports_clf1Model.pkl')
self.graphics_clf1 = joblib.load('./models/acd/lap/graphics_clf1Model.pkl')
self.mm_devs_clf1 = joblib.load('./models/acd/lap/mm_devs_clf1Model.pkl')
self.hardw_clf1 = joblib.load('./models/acd/lap/hardw_clf1Model.pkl')
self.os_clf1 = joblib.load('./models/acd/lap/os_clf1Model.pkl')
self.softw_clf1 = joblib.load('./models/acd/lap/softw_clf1Model.pkl')
self.warranty_clf1 = joblib.load('./models/acd/lap/warranty_clf1Model.pkl')
self.shipping_clf1 = joblib.load('./models/acd/lap/shipping_clf1Model.pkl')
self.support_clf1 = joblib.load('./models/acd/lap/support_clf1Model.pkl')
self.company_clf1 = joblib.load('./models/acd/lap/company_clf1Model.pkl')
self.general_clf1 = joblib.load('./models/acd/lap/general_clf1Model.pkl')
self.price_clf1 = joblib.load('./models/acd/lap/price_clf1Model.pkl')
self.quality_clf1 = joblib.load('./models/acd/lap/quality_clf1Model.pkl')
self.op_perf_clf1 = joblib.load('./models/acd/lap/op_perf_clf1Model.pkl')
self.usability_clf1 = joblib.load('./models/acd/lap/usability_clf1Model.pkl')
self.des_feats_clf1 = joblib.load('./models/acd/lap/des_feats_clf1Model.pkl')
self.portability_clf1 = joblib.load('./models/acd/lap/portability_clf1Model.pkl')
self.connectivity_clf1 = joblib.load('./models/acd/lap/connectivity_clf1Model.pkl')
self.misc_clf1 = joblib.load('./models/acd/lap/misc_clf1Model.pkl')
self.laptop_clf2 = joblib.load('./models/acd/lap/laptop_clf2Model.pkl')
self.display_clf2 = joblib.load('./models/acd/lap/display_clf2Model.pkl')
self.cpu_clf2 = joblib.load('./models/acd/lap/cpu_clf2Model.pkl')
self.mb_clf2 = joblib.load('./models/acd/lap/mb_clf2Model.pkl')
self.hd_clf2 = joblib.load('./models/acd/lap/hd_clf2Model.pkl')
self.memory_clf2 = joblib.load('./models/acd/lap/memory_clf2Model.pkl')
self.battery_clf2 = joblib.load('./models/acd/lap/battery_clf2Model.pkl')
self.power_clf2 = joblib.load('./models/acd/lap/power_clf2Model.pkl')
self.keyboard_clf2 = joblib.load('./models/acd/lap/keyboard_clf2Model.pkl')
self.mouse_clf2 = joblib.load('./models/acd/lap/mouse_clf2Model.pkl')
self.fans_clf2 = joblib.load('./models/acd/lap/fans_clf2Model.pkl')
self.opt_drives_clf2 = joblib.load('./models/acd/lap/opt_drives_clf2Model.pkl')
self.ports_clf2 = joblib.load('./models/acd/lap/ports_clf2Model.pkl')
self.graphics_clf2 = joblib.load('./models/acd/lap/graphics_clf2Model.pkl')
self.mm_devs_clf2 = joblib.load('./models/acd/lap/mm_devs_clf2Model.pkl')
self.hardw_clf2 = joblib.load('./models/acd/lap/hardw_clf2Model.pkl')
self.os_clf2 = joblib.load('./models/acd/lap/os_clf2Model.pkl')
self.softw_clf2 = joblib.load('./models/acd/lap/softw_clf2Model.pkl')
self.warranty_clf2 = joblib.load('./models/acd/lap/warranty_clf2Model.pkl')
self.shipping_clf2 = joblib.load('./models/acd/lap/shipping_clf2Model.pkl')
self.support_clf2 = joblib.load('./models/acd/lap/support_clf2Model.pkl')
self.company_clf2 = joblib.load('./models/acd/lap/company_clf2Model.pkl')
self.general_clf2 = joblib.load('./models/acd/lap/general_clf2Model.pkl')
self.price_clf2 = joblib.load('./models/acd/lap/price_clf2Model.pkl')
self.quality_clf2 = joblib.load('./models/acd/lap/quality_clf2Model.pkl')
self.op_perf_clf2 = joblib.load('./models/acd/lap/op_perf_clf2Model.pkl')
self.usability_clf2 = joblib.load('./models/acd/lap/usability_clf2Model.pkl')
self.des_feats_clf2 = joblib.load('./models/acd/lap/des_feats_clf2Model.pkl')
self.portability_clf2 = joblib.load('./models/acd/lap/portability_clf2Model.pkl')
self.connectivity_clf2 = joblib.load('./models/acd/lap/connectivity_clf2Model.pkl')
self.misc_clf2 = joblib.load('./models/acd/lap/misc_clf2Model.pkl')
def identifyQueryCategory(self, query):
print('Creating test feature vectors...')
test_sentences1 = []
test_sentences2 = []
words = (re.findall(r"[\w']+", query.lower())) #the unigrams list
sentence_without_stopwords = ""
for w in words:
if w not in stopwords:
sentence_without_stopwords = sentence_without_stopwords + " " + w
clean_words = acd_laptops_train.clean(sentence_without_stopwords).split()
#calculate the embedding of the words of the current sentence
sentence_vector_feats = []
words_with_embeds = []
for w in clean_words:
word_vector_feats = []
if w in self.w2v_model:
words_with_embeds.append(w)
for vector in self.w2v_model[w]:
word_vector_feats.append(vector)
sentence_vector_feats.append(word_vector_feats)
#calculate the centroid of the embeddings of the sentence (using idf)
centroid_feats = []
for vec_num in range(0,200):
sum_vectors = 0.
sum_idf = 0.
for w_index, word_vector in enumerate(sentence_vector_feats):
sum_vectors = sum_vectors + (word_vector[vec_num] * self.idf_dict[words_with_embeds[w_index]])
sum_idf = sum_idf + self.idf_dict[words_with_embeds[w_index]]
centroid = sum_vectors / (sum_idf) if sum_idf > 0. else 0.
centroid_feats.append(centroid)
normalized_centroid_feats = acd_laptops_train.normalize_horizontal(centroid_feats)
#compute the cosine similarity of the centroid of the sentence with the centroid of each category
distances = []
for category in self.category_centroids:
distances.append(acd_laptops_train.cosine_similarity(normalized_centroid_feats, category)[0][0])
stemmed_words = []
stemmed_bi_words = []
for w in words:
if w not in stopwords:
stemmed_words.append(self.stemmer.stem(w))
stemmed_bi_words.append(self.stemmer.stem(w))
stemmed_bigrams = nltk.bigrams(stemmed_bi_words)
stemmed_bigrams_list = []
for w in stemmed_bigrams:
stemmed_bigrams_list.append(w)
bigram_words = nltk.bigrams(words)
bigram_list = []
for w in bigram_words:
bigram_list.append(w)
tags = nltk.pos_tag(words)
tags_set = set()
for _, t in tags:
tags_set.add(t)
bitags = nltk.bigrams(list(tags_set))
bitag_list = []
for t in bitags:
bitag_list.append(t)
unigrams_feats = []
bigrams_feats = []
bipos_feats = []
stemmed_unigrams_feats = []
stemmed_bigrams_feats = []
#unigrams features
unigrams_feats = acd_laptops_train.assign_features(self.unigrams_lexica, words, False)
#bigrams features
bigrams_feats = acd_laptops_train.assign_features(self.bigrams_lexica, bigram_list, True)
#pos bigrams features
bipos_feats = acd_laptops_train.assign_features(self.bipos_lexica,bitag_list, True)
#stemmed_unigram features
stemmed_unigrams_feats = acd_laptops_train.assign_features(self.stemmed_unigrams_lexica, stemmed_words, False)
#stemmed_bigram features
stemmed_bigrams_feats = acd_laptops_train.assign_features(self.stemmed_bigrams_lexica, stemmed_bigrams_list, True)
test_sentences1.append(unigrams_feats + bigrams_feats + bipos_feats + stemmed_unigrams_feats + stemmed_bigrams_feats)
test_sentences2.append(normalized_centroid_feats + distances)
test_features1 = np.asarray(test_sentences1)
test_features2 = np.asarray(test_sentences2)
aspect_categories = []
print('Done!')
print('Predicting categories...')
categories = []
for i, test_fvector in enumerate(test_features1):
laptop_pred1 = self.laptop_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
display_pred1 = self.display_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
cpu_pred1 = self.cpu_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
mb_pred1 = self.mb_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
hd_pred1 = self.hd_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
memory_pred1 = self.memory_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
battery_pred1 = self.battery_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
power_pred1 = self.power_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
keyboard_pred1 = self.keyboard_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
mouse_pred1 = self.mouse_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
fans_pred1 = self.fans_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
opt_drives_pred1 = self.opt_drives_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
ports_pred1 = self.ports_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
graphics_pred1 = self.graphics_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
mm_devs_pred1 = self.mm_devs_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
hardw_pred1 = self.hardw_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
os_pred1 = self.os_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
softw_pred1 = self.softw_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
warranty_pred1 = self.warranty_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
shipping_pred1 = self.shipping_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
support_pred1 = self.support_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
company_pred1 = self.company_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
general_pred1 = self.general_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
price_pred1 = self.price_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
quality_pred1 = self.quality_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
op_perf_pred1 = self.op_perf_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
usability_pred1 = self.usability_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
des_feats_pred1 = self.des_feats_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
portability_pred1 = self.portability_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
connectivity_pred1 = self.connectivity_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
misc_pred1 = self.misc_clf1.predict_proba(test_fvector.reshape(1,-1))[0,1]
laptop_pred2 = self.laptop_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
display_pred2 = self.display_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
cpu_pred2 = self.cpu_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
mb_pred2 = self.mb_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
hd_pred2 = self.hd_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
memory_pred2 = self.memory_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
battery_pred2 = self.battery_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
power_pred2 = self.power_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
keyboard_pred2 = self.keyboard_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
mouse_pred2 = self.mouse_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
fans_pred2 = self.fans_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
opt_drives_pred2 = self.opt_drives_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
ports_pred2 = self.ports_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
graphics_pred2 = self.graphics_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
mm_devs_pred2 = self.mm_devs_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
hardw_pred2 = self.hardw_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
os_pred2 = self.os_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
softw_pred2 = self.softw_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
warranty_pred2 = self.warranty_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
shipping_pred2 = self.shipping_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
support_pred2 = self.support_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
company_pred2 = self.company_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
general_pred2 = self.general_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
price_pred2 = self.price_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
quality_pred2 = self.quality_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
op_perf_pred2 = self.op_perf_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
usability_pred2 = self.usability_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
des_feats_pred2 = self.des_feats_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
portability_pred2 = self.portability_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
connectivity_pred2 = self.connectivity_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
misc_pred2 = self.misc_clf2.predict_proba(test_features2[i].reshape(1,-1))[0,1]
entity_prob = {"laptop": (laptop_pred1+laptop_pred2)/2, "display": (display_pred1+display_pred2)/2, "cpu": (cpu_pred1+cpu_pred2)/2,
"motherboard": (mb_pred1+mb_pred2)/2, "hard_disc": (hd_pred1+hd_pred2)/2,
"memory": (memory_pred1+memory_pred2)/2, "battery": (battery_pred1+battery_pred2)/2,
"power_supply": (power_pred1+power_pred2)/2, "keyboard": (keyboard_pred1+keyboard_pred2)/2,
"mouse": (mouse_pred1+mouse_pred2)/2,
"fans_cooling": (fans_pred1+fans_pred2)/2, "optical_drives": (opt_drives_pred1+opt_drives_pred2)/2,
"ports": (ports_pred1+ports_pred2)/2, "graphics": (graphics_pred1+graphics_pred2)/2,
"multimedia_devices": (mm_devs_pred1+mm_devs_pred2)/2, "hardware": (hardw_pred1+hardw_pred2)/2,
"os": (os_pred1+os_pred2)/2, "software": (softw_pred1+softw_pred2)/2, "warranty": (warranty_pred1+warranty_pred2)/2,
"shipping": (shipping_pred1+shipping_pred2)/2, "support": (support_pred1+support_pred2)/2,
"company": (company_pred1+company_pred2)/2}
attr_prob = {"general": (general_pred1+general_pred2)/2, "price": (price_pred1+price_pred2)/2, "quality": (quality_pred1+quality_pred2)/2,
"operation_performance": (op_perf_pred1+op_perf_pred2)/2, "usability": (usability_pred1+usability_pred2)/2,
"design_features": (des_feats_pred1+des_feats_pred2)/2,
"portability": (portability_pred1+portability_pred2)/2, "connectivity": (connectivity_pred1+connectivity_pred2)/2,
"miscellaneous": (misc_pred1+misc_pred2)/2}
sorted_entity_prob = sorted(entity_prob.items(), key=operator.itemgetter(1), reverse=True)
sorted_attr_prob = sorted(attr_prob.items(), key=operator.itemgetter(1), reverse=True)
for entity in sorted_entity_prob:
for attr in sorted_attr_prob:
if entity[1] > 0.4 and attr[1] > 0.4:
category = entity[0]+'#'+attr[0]
for c in self.cat_dict:
if category == c and self.cat_dict[c] > 0:
categories.append(category.upper())
print('Done!')
return categories