def create_similarity_features6(train, row, id=None):
clr_print(id, row['product_title'])
tx1, dx1 = get_str_for_query6(train, row['query'], row['product_title'], row['product_description'], 1, id)
tx2, dx2 = get_str_for_query6(train, row['query'], row['product_title'], row['product_description'], 2, id)
tx3, dx3 = get_str_for_query6(train, row['query'], row['product_title'], row['product_description'], 3, id)
tx4, dx4 = get_str_for_query6(train, row['query'], row['product_title'], row['product_description'], 4, id)
our_tx = ' '.join(process_str(row['product_title']))
our_dx = ' '.join(process_str(row['product_description']))
rez = []
for ngrams in [get_ngrams(our_tx, 2),
get_ngrams(our_tx, 4),
get_ngrams(our_tx, 6),
get_ngrams(our_tx, 8),
]:
for fx in [tx1, dx1, tx2, dx2, tx3, dx3, tx4, dx4]:
c = 1
for ngram in ngrams:
for f in fx:
c+= f.count(ngram)
c /= len(ngrams)+1
rez.append(c)
return rez
def create_similarity_features7(train, row, id=None):
clr_print(id, row['product_title'])
tx1 = get_str_for_query7(train, row['query'], 1, id)
tx2 = get_str_for_query7(train, row['query'], 2, id)
tx3 = get_str_for_query7(train, row['query'], 3, id)
tx4 = get_str_for_query7(train, row['query'], 4, id)
our_tx = set(process_str_replace(row['product_names']))
return len(tx1 & our_tx), len(tx2 & our_tx), len(tx3 & our_tx), len(tx4 & our_tx)