def check_for_noun_adj(depend_dict, pos_dict,final_score,neg_words):
# getting the score and stopwords dictionary
sd,stopwords = get_dict()
flag = 0
stemmer3 = WordNetLemmatizer()
for value in depend_dict.values():
for j in range(len(value)):
score1 = 100
score2 = 100
li = value[j]
if "nsubj" in li[0] or "mod" in li[0]:
meaning = 0.2
n1 = li[1]
n2 = li[3]
m1, m2 = check_for_negative(n1,n2,li[2],li[4],neg_words)
try:
t1 = pos_dict[n1]
except KeyError:
# print n1 + ' is not there!!'
flag = 1
try:
t2 = pos_dict[n2]
except KeyError:
# print n2 + ' is not there!!'
flag = 1
if (flag != 1 and n1.lower() not in stopwords
and n2.lower() not in stopwords):
score1 = getting_sentiment(n1.lower(),t1)
if score1 != 100:
score1 = float(score1) * float(m1)
score2 = getting_sentiment(n2.lower(),t2)
if score2 != 100:
score2 = float(score2) * float(m2)
if score1 != 100 or score2 != 100:
if 'NN' in t1 or 'NN' in t2:
if 'JJ' in t1 or 'JJ' in t2:
meaning = 1
# print n1 + ' and ' + n2 + ' appear to be meaningful...'
elif ('VB' in t1 or 'VB' in t2
or ('NN' in t1 and 'NN' in t2)):
# print n1 + ' and ' + n2 + ' appear to be less meaningful...'
meaning = 0.8
else:
meaning = 0.2
if score1 != 100 and score2 == 100:
apply_score(li,n2,score1,final_score,meaning,n1,t2,t1)
print n1,n2
if score2 != 100 and score1 == 100:
print n2,n1
apply_score(li,n1,score2,final_score,meaning,n2,t1,t2)
elif score2 != 100 and score1 != 100:
if 'NN' in t1 and 'JJ' in t2:
# print n1,n2
apply_score(li,n1,score2,final_score,meaning,n2,t1,t2)
elif 'JJ' in t1 and 'NN' in t2:
apply_score(li,n2,score1,final_score,meaning,n1,t2,t1)
# print n1,n2
elif 'NN' in t1:
apply_score(li,n1,score2,final_score,meaning,n2,t1,t2)
# print n1,n2
elif 'NN' in t2:
apply_score(li,n2,score1,final_score,meaning,n1,t2,t1)
# print n1,n2
else:
# print 'The scores are not present for ' + n1 + ' and ' + n2
pass
# checking for direct object or dependency...
if 'dobj' in li[0] or 'dep' in li[0]:
n1 = li[1]
n2 = li[3]
m1, m2 = check_for_negative(n1,n2,li[2],li[4],neg_words)
t1 = pos_dict[n1]
t2 = pos_dict[n2]
score1 = 100
score2 = 100
score1 = getting_sentiment(n1.lower(),t1)
if score1 != 100:
score1 = float(score1) * float(m1)
score2 = getting_sentiment(n2.lower(),t2)
if score2 != 100:
score2 = float(score2) * float(m2)
if score1 != 100 or score2 != 100:
if (n1.lower() not in stopwords and
n2.lower() not in stopwords):
if 'NN' in t1 or 'NN' in t2:
if 'JJ' in t1 or 'JJ' in t2:
meaning = 1
# print n1,t1 + ' and ' + n2,t2 + ' adjective-noun as direct object...'
else:
if ('VB' in t1 or 'VB' in t2 or
('NN' in t1 and 'NN' in t2)):
meaning = 0.8
# print n1,t1 + ' and ' + n2,t2 + ' as direct object...'
else:
meaning = 0.2
# print 'no noun occurance'
if score2 != 100 and score1 == 100:
apply_score(li,n1,score2,final_score,meaning,n2,t1,t2)
elif score1 != 100 and score2 == 100:
apply_score(li,n2,score1,final_score,meaning,n1,t2,t1)
elif score1 != 100 and score2 != 100:
if 'NN' in t1 and 'JJ' in t2:
apply_score(li,n1,score2,final_score,meaning,n2,t1,t2)
elif 'JJ' in t1 and 'NN' in t2:
apply_score(li,n2,score1,final_score,meaning,n1,t2,t1)
elif score1 > score2:
apply_score(li,n2,score1,final_score,meaning,n1,t2,t1)
elif score2 >= score1:
apply_score(li,n1,score2,final_score,meaning,n2,t1,t2)
else:
print '-----------stopwords-----------'
def check_for_noun_adj(depend_dict, pos_dict, final_score, neg_words):
# getting the score and stopwords dictionary
sd, stopwords = get_dict()
flag = 0
stemmer3 = WordNetLemmatizer()
for value in depend_dict.values():
for j in range(len(value)):
score1 = 100
score2 = 100
li = value[j]
if "nsubj" in li[0] or "mod" in li[0]:
meaning = 0.2
n1 = li[1]
n2 = li[3]
m1, m2 = check_for_negative(n1, n2, li[2], li[4], neg_words)
try:
t1 = pos_dict[n1]
except KeyError:
# print n1 + ' is not there!!'
flag = 1
try:
t2 = pos_dict[n2]
except KeyError:
# print n2 + ' is not there!!'
flag = 1
if (flag != 1 and n1.lower() not in stopwords
and n2.lower() not in stopwords):
score1 = getting_sentiment(n1.lower(), t1)
if score1 != 100:
score1 = float(score1) * float(m1)
score2 = getting_sentiment(n2.lower(), t2)
if score2 != 100:
score2 = float(score2) * float(m2)
if score1 != 100 or score2 != 100:
if 'NN' in t1 or 'NN' in t2:
if 'JJ' in t1 or 'JJ' in t2:
meaning = 1
# print n1 + ' and ' + n2 + ' appear to be meaningful...'
elif ('VB' in t1 or 'VB' in t2
or ('NN' in t1 and 'NN' in t2)):
# print n1 + ' and ' + n2 + ' appear to be less meaningful...'
meaning = 0.8
else:
meaning = 0.2
if score1 != 100 and score2 == 100:
apply_score(li, n2, score1, final_score, meaning,
n1, t2, t1)
print n1, n2
if score2 != 100 and score1 == 100:
print n2, n1
apply_score(li, n1, score2, final_score, meaning,
n2, t1, t2)
elif score2 != 100 and score1 != 100:
if 'NN' in t1 and 'JJ' in t2:
# print n1,n2
apply_score(li, n1, score2, final_score,
meaning, n2, t1, t2)
elif 'JJ' in t1 and 'NN' in t2:
apply_score(li, n2, score1, final_score,
meaning, n1, t2, t1)
# print n1,n2
elif 'NN' in t1:
apply_score(li, n1, score2, final_score,
meaning, n2, t1, t2)
# print n1,n2
elif 'NN' in t2:
apply_score(li, n2, score1, final_score,
meaning, n1, t2, t1)
# print n1,n2
else:
# print 'The scores are not present for ' + n1 + ' and ' + n2
pass
# checking for direct object or dependency...
if 'dobj' in li[0] or 'dep' in li[0]:
n1 = li[1]
n2 = li[3]
m1, m2 = check_for_negative(n1, n2, li[2], li[4], neg_words)
t1 = pos_dict[n1]
t2 = pos_dict[n2]
score1 = 100
score2 = 100
score1 = getting_sentiment(n1.lower(), t1)
if score1 != 100:
score1 = float(score1) * float(m1)
score2 = getting_sentiment(n2.lower(), t2)
if score2 != 100:
score2 = float(score2) * float(m2)
if score1 != 100 or score2 != 100:
if (n1.lower() not in stopwords
and n2.lower() not in stopwords):
if 'NN' in t1 or 'NN' in t2:
if 'JJ' in t1 or 'JJ' in t2:
meaning = 1
# print n1,t1 + ' and ' + n2,t2 + ' adjective-noun as direct object...'
else:
if ('VB' in t1 or 'VB' in t2
or ('NN' in t1 and 'NN' in t2)):
meaning = 0.8
# print n1,t1 + ' and ' + n2,t2 + ' as direct object...'
else:
meaning = 0.2
# print 'no noun occurance'
if score2 != 100 and score1 == 100:
apply_score(li, n1, score2, final_score, meaning,
n2, t1, t2)
elif score1 != 100 and score2 == 100:
apply_score(li, n2, score1, final_score, meaning,
n1, t2, t1)
elif score1 != 100 and score2 != 100:
if 'NN' in t1 and 'JJ' in t2:
apply_score(li, n1, score2, final_score,
meaning, n2, t1, t2)
elif 'JJ' in t1 and 'NN' in t2:
apply_score(li, n2, score1, final_score,
meaning, n1, t2, t1)
elif score1 > score2:
apply_score(li, n2, score1, final_score,
meaning, n1, t2, t1)
elif score2 >= score1:
apply_score(li, n1, score2, final_score,
meaning, n2, t1, t2)
else:
print '-----------stopwords-----------'
from operator import itemgetter
import itertools
import collections
import dpath.util
from classifier import get_lookup_dict,get_trained_classifier,check_in_dic
from final_scores import final_scores
java_path = "/usr/lib/jvm/java-8-oracle/jre/bin/java" # replace this
os.environ['JAVAHOME'] = java_path
os.environ['STANFORD_PARSER'] = '/home/farhan/Recommendation-system/stanford-ner-2015-12-09'
os.environ['STANFORD_MODELS'] = '/home/farhan/Recommendation-system/stanford-ner-2015-12-09/classifiers'
# defining global parameters
score_dic,stopwords = get_dict()
neg_prefix = ['not','none','nor','n\'t']
# final_score = {}
# compound_word_dic = {}
# compound_word_list = []
# neg_words = []
# checking for any dish present...
# combine compound word
def compound_word(li):
# print li
word = []
st = ''
import itertools
import collections
import dpath.util
from classifier import get_lookup_dict, get_trained_classifier, check_in_dic
from final_scores import final_scores
java_path = "/usr/lib/jvm/java-8-oracle/jre/bin/java" # replace this
os.environ['JAVAHOME'] = java_path
os.environ[
'STANFORD_PARSER'] = '/home/farhan/Recommendation-system/stanford-ner-2015-12-09'
os.environ[
'STANFORD_MODELS'] = '/home/farhan/Recommendation-system/stanford-ner-2015-12-09/classifiers'
# defining global parameters
score_dic, stopwords = get_dict()
neg_prefix = ['not', 'none', 'nor', 'n\'t']
# final_score = {}
# compound_word_dic = {}
# compound_word_list = []
# neg_words = []
# checking for any dish present...
# combine compound word
def compound_word(li):
# print li
word = []
st = ''