tokens = []
for line in f:
if position == 0:
if '<top>' in line:
position = 1
else:
if '</top>' in line:
queries.append([num, tokens])
num = -1
tokens = []
position = 0
elif '<num>' in line:
num = tokenize.numeric_norm(line)[0][0]
elif '<title>' in line:
line = line.replace('Topic:', '')
token_list, query_position = tokenize.process_line(line,0)
position = query_position
tokens += token_list
# process queries
# token is of format: (word, position, tf) => (word, position, tf, stemmed_word, idf)
processed_queries = []
for query in queries:
token_list = query[1]
new_token_list = []
phrases = find_phrases(token_list)
for token in token_list:
if token[0] not in stop_words:
stemmed = tokenize.ps.stem(token[0]).encode('utf-8')
idf = get_idf(token[0], lexicons[0])
if idf == 0: