def train_feature_gen():
ap_pairs = []
labels = []
print (DATA['Train'])
with open(DATA['Train'], 'r') as f:
reader = csv.DictReader(f)
for row in reader:
confirmed_paper_ids = [paper_id for paper_id in row['ConfirmedPaperIds'].strip().split(' ') if paper_id.__len__() > 0]
deleted_paper_ids = [paper_id for paper_id in row['DeletedPaperIds'].strip().split(' ') if paper_id.__len__() > 0]
ap_pairs += [(row['AuthorId'], pid) for pid in confirmed_paper_ids]
labels += [1] * len(confirmed_paper_ids)
ap_pairs += [(row['AuthorId'], pid) for pid in deleted_paper_ids]
labels += [-1] * len(deleted_paper_ids)
# for pair in ap_pairs:
# print (pair[0], pair[1])
# print (len(ap_pairs))
# sys.exit(0)
f_bcmk = features.benchmark(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'], paper_csv=DATA['Paper'])
f_yrre = features.years_related(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'], paper_csv=DATA['Paper'])
f_strdist = features.string_distances(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'], author_csv=DATA['Author'])
f_coauth = features.coauthor_related(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'])
with open(sys.argv[1], 'w') as g:
for i in range(len(labels)):
print(labels[i], end='', file=g)
print('', *f_bcmk[i], sep=' ', end='', file=g)
print('', *f_yrre[i], sep=' ', end='', file=g)
print('', *f_strdist[i], sep=' ', end='', file=g)
print('', *f_coauth[i], sep=' ', end='', file=g)
print('', file=g)
def valid_feature_gen():
ap_pairs = []
labels = []
with open(DATA['Valid'], 'r') as f:
reader = csv.DictReader(f)
for row in reader:
paper_ids = row['PaperIds'].strip().split(' ')
ap_pairs += [(row['AuthorId'], pid) for pid in paper_ids]
labels += [0] * len(paper_ids)
f_bcmk = features.benchmark(ap_pairs=ap_pairs,
paper_author_csv=DATA['PaperAuthor'],
paper_csv=DATA['Paper'])
f_yrre = features.years_related(ap_pairs=ap_pairs,
paper_author_csv=DATA['PaperAuthor'],
paper_csv=DATA['Paper'])
f_strdist = features.string_distances(ap_pairs=ap_pairs,
paper_author_csv=DATA['PaperAuthor'],
author_csv=DATA['Author'])
f_coauth = features.coauthor_related(ap_pairs=ap_pairs,
paper_author_csv=DATA['PaperAuthor'])
with open(sys.argv[2], 'w') as g:
for i in range(len(labels)):
print(labels[i], end='', file=g)
print('', *f_bcmk[i], sep=' ', end='', file=g)
print('', *f_yrre[i], sep=' ', end='', file=g)
print('', *f_strdist[i], sep=' ', end='', file=g)
print('', *f_coauth[i], sep=' ', end='', file=g)
print('', file=g)
def valid_feature_gen():
ap_pairs = []
labels = []
with open(DATA['Valid'], 'r') as f:
reader = csv.DictReader(f)
for row in reader:
paper_ids = row['PaperIds'].strip().split(' ')
ap_pairs += [(row['AuthorId'], pid) for pid in paper_ids]
labels += [0] * len(paper_ids)
f_bcmk = features.benchmark(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'], paper_csv=DATA['Paper'])
f_yrre = features.years_related(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'], paper_csv=DATA['Paper'])
f_strdist = features.string_distances(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'], author_csv=DATA['Author'])
f_coauth = features.coauthor_related(ap_pairs=ap_pairs, paper_author_csv=DATA['PaperAuthor'])
with open(sys.argv[2], 'w') as g:
for i in range(len(labels)):
print(labels[i], end='', file=g)
print('', *f_bcmk[i], sep=' ', end='', file=g)
print('', *f_yrre[i], sep=' ', end='', file=g)
print('', *f_strdist[i], sep=' ', end='', file=g)
print('', *f_coauth[i], sep=' ', end='', file=g)
print('', file=g)