with open("most_frequent_abbreviations.csv", "r") as csvfile:

abbreviations = []

readCSV = csv.reader(csvfile, delimiter = ',')

for row in readCSV:

abbreviations.append(row[0])

abbreviations[2] = 'MCQ'

abbreviations[12] = 'PYQ'

if len(a) == 1:

if b[0].lower() == a[0].lower():

return True

elif len(a) == 2:

if len(b) >= 2 and b[0].lower() == a[0].lower and b[1].lower() == a[1].lower():

return True

all_initials = []

# Tokenise into initials

for word in reduced_abbreviations:

initials = []

i = 0

while i < len(word):

if word[i] == '.':

i += 1

if i + 1 < len(word) and word[i+1].islower():

initials.append(str(word[i] + word[i+1]))

i+=2

else:

initials.append(word[i])

i += 1

initials_1 = []

for initial in initials:

initials_1.append(initial.lower())

all_initials.append(initials_1)

with open('abbreviation_data_set.csv') as csvfile:

descriptions = []

names = []

readCSV = csv.reader(csvfile, delimiter=',')

for row in readCSV:

if len(row) > 1:

descriptions.append(cleanse(row[1]))

names.append(cleanse(row[0]))

index = 0

# print(all_initials[2])

abbrevation_expansions = {}

for initials in all_initials:

index += 1

m = len(initials)

abbreviation = ''.join(initials)

abbrevation_expansions[abbreviation] = []

matchings = []

print(index, abbreviation)

regex = '^' + '.* '.join(initials) + '.*$'

r = re.compile(regex)

matchings = []

for delta in range(0, threshold + 1):

if len(matchings) > 0:

break

for description in descriptions:

n = m + delta

grams = ngrams(description.split(), n)

for gram in grams:

flag = 0

if abbreviation in gram:

continue

for word in gram:

if word.startswith(abbreviation):

flag = 1

break

if flag == 1:

continue

pattern = ' '.join(gram)

if r.match(pattern):

matchings.append(pattern)

for name in names:

n = m + delta

grams = ngrams(name.split(), n)

for gram in grams:

flag = 0

if abbreviation in gram:

continue

for word in gram:

if word.startswith(abbreviation):

flag = 1

break

if flag == 1:

continue

pattern = ' '.join(gram)

if r.match(pattern):

matchings.append(pattern)

frequent_matchings = Counter(matchings)

i = 0

for matching in frequent_matchings.most_common():

abbrevation_expansions[abbreviation].append(matching[0])

i += 1

if i == 5:

break

frequent_abbreviations = most_frequent_abbreviations()

all_initials = preprocess_abbreviations(frequent_abbreviations)

descriptions, names = preprocess_descriptions()

abbreviation_expansions = find_proximal_expansion(all_initials, descriptions, names, threshold)

` schwartz_hearst_abbreviation_expansions = schwartz_hearst.extract_abbreviation_definition_pairs('./abbreviation_data_set.csv')

fields = ['Acronym', 'Expansions']

with open("final_merged_abbreviations.csv", "w") as csvfile:

csvwriter = csv.writer(csvfile)

csvwriter.writerow(fields)

merged_abbreviations = {}

for pairs in schwartz_hearst_abbreviation_expansions.keys():

merged_abbreviations[pairs] = []

merged_abbreviations[pairs].append(schwartz_hearst_abbreviation_expansions[pairs])

for abbreviation in frequent_abbreviations:

if abbreviation in merged_abbreviations:

left = 3

if abbreviation.lower() in abbreviation_expansions:

for word in abbreviation_expansions[abbreviation.lower()]:

if word.lower() == merged_abbreviations[abbreviation][0].lower():

continue

left -= 1

merged_abbreviations[abbreviation].append(word)

if left == 0:

break

else:

left = 4

merged_abbreviations[abbreviation] = []

if abbreviation.lower() in abbreviation_expansions:

for word in abbreviation_expansions[abbreviation.lower()]:

left -= 1

merged_abbreviations[abbreviation].append(word)

if left == 0:

break

for key in merged_abbreviations.keys():

row = []

row.append(key)

for word in merged_abbreviations[key]:

row.append(word)