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dblp_data.py
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dblp_data.py
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import numpy as np
import pandas as pd
import sys
import os
class Dblp2node_link:
def __init__(self):
self.input_paper_author = {}
self.input_author_paper = {}
self.input_author_name = {}
self.input_name_author = {}
self.venue = {}
self.selected_author = set()
self.selected_papaer = set()
self.selected_paper_venue = {}
self.reference_list = []
self.sanity_check = set()
def read_author(self,filename):
i = 0
with open(filename) as input_author:
for line in input_author:
if i == 0:
i+=1
print(line)
continue
toks = line.replace('\n','').replace(' ','_').split(',')
i+=1
if toks[1] not in self.input_paper_author:
self.input_paper_author[toks[1]] = set()
if toks[0] not in self.input_author_paper:
self.input_author_paper[toks[0]] = set()
self.input_paper_author[toks[1]].add(toks[0])
self.input_author_paper[toks[0]].add(toks[1])
def read_author_name(self,filename):
i = 0
with open(filename) as input_person:
for line in input_person:
if i == 0:
i+=1
continue
toks = line.replace('\n','').split(',')
i+=1
self.input_author_name[toks[0]] = toks[1]
self.input_name_author[toks[1].replace(' ','_')] = toks[0]
def read_paper_venue_year(self, filename, selected_venue):
paper_table = pd.read_csv(filename)
abbreviation_flag = True
if len(selected_venue) < 1:
abbreviation_flag = False
venue_file = filename.replace('paper','venue')
with open(venue_file) as venues:
for line in venues:
venue_name = line.replace('\n','')
self.venue[venue_name] = set()
print(len(self.venue), abbreviation_flag)
if abbreviation_flag:
self.venue['ECML_PKDD'] =set()
self.venue['SIGMOD_PODS'] =set()
for venue in selected_venue:
self.venue[venue] = set()
selected_paper_table = paper_table[paper_table['venue'].str.contains(venue)]
if venue == 'KDD':
selected_paper_table = selected_paper_table[~selected_paper_table['venue'].str.contains('PAKDD')]
selected_paper_table = selected_paper_table[~selected_paper_table['venue'].str.contains('PKDD')]
elif venue == 'SDM':
selected_paper_table = selected_paper_table[~selected_paper_table['venue'].str.contains('WSDM')]
for index, row in selected_paper_table.iterrows():
if row['id'] in self.selected_paper_venue:
if venue == 'PKDD' and self.selected_paper_venue[row['id']] == 'ECML':
self.selected_paper_venue[row['id']] = 'ECML_PKDD'
continue
elif venue == 'PODS' and self.selected_paper_venue[row['id']] == 'SIGMOD':
self.selected_paper_venue[row['id']] = 'SIGMOD_PODS'
continue
print(self.selected_paper_venue[row['id']], row['venue'],venue)
self.selected_paper_venue[row['id']] = venue
self.selected_papaer.add(row['id'])
else:
for venue in self.venue:
selected_paper_table = paper_table[paper_table['venue'] == venue]
# print(selected_paper_table.shape)
for index, row in selected_paper_table.iterrows():
self.selected_paper_venue[row['id']] = venue
self.selected_papaer.add(row['id'])
def back_filter_read_ref(self,filename):
'''
Selecting authors for filtered paper and read P-P link
'''
for paper in self.selected_papaer:
if str(paper) in self.input_paper_author:
self.selected_author |= self.input_paper_author[str(paper)]
else:
self.sanity_check.add(str(paper))
i = 0
with open(filename) as input_reference:
for line in input_reference:
if i == 0 :
i+=1
continue
toks = line.replace('\n','').split(',')
if int(toks[0]) in self.selected_papaer and int(toks[1]) in self.selected_papaer:
self.reference_list.append(str(toks[0]) + '\t' + str(toks[1]))
i+=1
print(len(self.reference_list))
def filter_by_author(self, author_file):
temp_selected_author = set()
with open(author_file) as author_list:
for line in author_list:
if line.replace('\n','') in self.input_name_author:
temp_selected_author.add(self.input_name_author[line.replace('\n','')])
temp_selected_paper = set()
missing_count = 0
for author in temp_selected_author:
if author in self.input_author_paper:
temp_selected_paper |= self.input_author_paper[author]
else:
missing_count+=1
print(missing_count, 'in groud truth not in dataset')
temp_reference_list = []
for token in self.reference_list:
toks = token.split('\t')
if str(toks[0]) in temp_selected_paper and str(toks[1]) in temp_selected_paper:
temp_reference_list.append(token)
self.selected_papaer = temp_selected_paper
self.selected_author = temp_selected_author
self.reference_list = temp_reference_list
def output_to_file(self,save_dir):
if not os.path.exists(save_dir):
os.makedirs(save_dir)
node_list = []
link_list = list(self.reference_list)
print('p-p edge count',len(link_list))
refined_author = set()
author_count = 0
for paper in self.selected_papaer:
node_list.append(str(paper) + '\tp')
if str(paper) not in self.input_paper_author:
# print(paper)
continue
for author_id in self.input_paper_author[str(paper)]:
if author_id in self.selected_author:
link_list.append(str(self.input_author_name[author_id].replace(' ','_'))+'\t'+str(paper))
link_list.append(str(paper)+'\t'+str(self.input_author_name[author_id].replace(' ','_')))
print('p-p+p-a edge count',len(link_list))
for author in self.selected_author:
if author not in self.input_author_name: continue
refined_author.add(str(self.input_author_name[author].replace(' ','_')))
for final_author in refined_author:
node_list.append(final_author + '\ta')
author_count+=1
for venue in self.venue:
node_list.append(str(venue.replace(' ','_')) + '\tv')
for paper in self.selected_paper_venue:
link_list.append(str(paper) +'\t'+ str(self.selected_paper_venue[paper]))
link_list.append(str(self.selected_paper_venue[paper]) +'\t'+ str(paper))
print('node count:',len(node_list),';','author count:',author_count,';','edge count:',len(link_list))
with open(save_dir+'node.dat','w') as node_output:
for node in node_list:
node_output.write(node+'\n')
with open(save_dir+'link.dat','w') as link_output:
for link in link_list:
link_output.write(link+'\n')
def sanity_check_func(self,filename):
i = 0
with open(filename) as input_author:
for line in input_author:
if i == 0:
i+=1
continue
toks = line.replace('\n','').split(',')
i+=1
if toks[1] in self.sanity_check:
print('WRONG',toks)
# numwalks = int(sys.argv[1])
"""The following data is extracted from Aminer database. Please follow their instructions to
select the year range. After selecting year, you could algo select venues as you want.
"""
authorpath = "./data/author-1900-2020.csv"
refpath = "./data/refs-1900-2020.csv"
paperpath = "./data/paper-1900-2020.csv"
personpath = "./data/person-1900-2020.csv"
groundtruth = "./data/vocab-label.txt"
# selected_venue = ['AAAI','CVPR','ECML','IJCAI','SIGMOD','VLDB','PODS','EDBT','ICDE','ICDM','KDD','PAKDD','PKDD','ECIR','SIGIR','WSDM','WWW','CIKM']
# selected_venue = ['ICDM','KDD','PAKDD','PKDD','WSDM','WWW','CIKM']
# selected_venue = ['KDD','ECML','PKDD']
selected_venue = []
save_dir = './data/dblp/'
def main():
dblp2data =Dblp2node_link()
dblp2data.read_author(authorpath)
dblp2data.read_author_name(personpath)
dblp2data.read_paper_venue_year(paperpath,selected_venue)
dblp2data.back_filter_read_ref(refpath)
print('Begin filtering authors')
dblp2data.filter_by_author(groundtruth)
dblp2data.output_to_file(save_dir)
dblp2data.sanity_check_func(authorpath)
main()