def filterByOp(self,clone):
opStr1 = ""
opStr2 = ""
indx1,start1,end1 = clone[1]
indx2,start2,end2 = clone[2]
for i in range(start1,end1+1):
opStr1 += str(self.op1_hash.get(i,-1))
for i in range(start2,end2+1):
opStr2 += str(self.op2_hash.get(i,-1))
if config.DEBUG is True:
print "start1 = %d, end1 = %d, ops = %s" % (start1,end1,opStr1)
print "start2 = %d, end2 = %d, ops = %s" % (start2,end2,opStr2)
# if ((self.hasChanged(opStr1) is False) or
# (self.hasChanged(opStr2) is False)):
if not (self.hasChanged(opStr1) and self.hasChanged(opStr2)):
return None
idx = NGram(N=config.NGRAM)
ngram1 = list(idx.ngrams(opStr1))
ngram2 = list(idx.ngrams(opStr2))
metric = self.compareList(ngram1,ngram2)
return metric
def test():
filter = opFilter()
opStr1 = "nnn+"
opStr2 = "nn+"
idx = NGram(N=config.NGRAM)
l1 = list(idx.ngrams(opStr1))
l2 = list(idx.ngrams(opStr2))
print filter.compareList(l1,l2)
def ngram_compare(a, b, N):
ngram = NGram(N=N)
A = set(ngram.ngrams(a))
B = set(ngram.ngrams(b))
return len(A & B) / len(A | B)
def main():
# NGramで解析する単位の設定
index = NGram(N=2)
list_recruit = []
count = [0] * 10
# projects_hit_count = [[count_hits,id]]
projects_hit_count = []
# DB
connector = psycopg2.connect(host="localhost", database="wantedly")
cursor = connector.cursor()
# 質問読み込み
print "質問："
input_q = raw_input().decode("utf-8")
for input_q in index.ngrams(index.pad(input_q)):
# 入力されたメッセージを含まれたものを全て出すため
input_q = "%" + input_q + "%"
# SQL
sql = "select id,company_id,title,description,location,keywords from projects where looking_for like '%s'" % input_q
# print sql
cursor.execute(sql)
result = cursor.fetchall()
for row in result:
count[row[0]] = count[row[0]] + 1
for i in range(0, 10):
if count[i] != 0:
projects_hit_count.append([count[i], i])
# ヒット数高い順
projects_hit_count.sort()
projects_hit_count.reverse()
print projects_hit_count
if len(projects_hit_count) == 0:
a = 0
# 当てはめる募集がなかった場合
print "やりたい仕事がありますか？それか興味ある分野とは？"
elif len(projects_hit_count) < 3:
a = len(projects_hit_count)
print "\nこんにちは、今のような募集がありますが、いかがですか？"
else:
a = 3
print "\nこんにちは、今のような募集がありますが、いかがですか？"
for i in range(0, a):
sql = "select id,company_id,title,description,location,keywords from projects where id ='%s'" % projects_hit_count[
i][1]
# print sql
cursor.execute(sql)
result = cursor.fetchall()
for row in result:
print str(i + 1) + "."
print str(row[2])
print str(row[5])
connector.commit()
cursor.close()
connector.close()
def main():
# NGramで解析する単位の設定
index = NGram(N=2)
list_recruit = []
count = [0] * 10
# projects_hit_count = [[count_hits,id]]
projects_hit_count = []
# DB
connector = psycopg2.connect(host="localhost",database="wantedly")
cursor = connector.cursor()
# 質問読み込み
print "質問："
input_q = raw_input().decode("utf-8")
for input_q in index.ngrams(index.pad(input_q)):
# 入力されたメッセージを含まれたものを全て出すため
input_q = "%"+input_q+"%"
# SQL
sql="select id,company_id,title,description,location,keywords from projects where looking_for like '%s'"%input_q
# print sql
cursor.execute(sql)
result = cursor.fetchall()
for row in result:
count[row[0]] = count[row[0]] +1
for i in range(0,10):
if count[i] != 0:
projects_hit_count.append([count[i],i])
# ヒット数高い順
projects_hit_count.sort()
projects_hit_count.reverse()
print projects_hit_count
if len(projects_hit_count) ==0:
a=0
# 当てはめる募集がなかった場合
print "やりたい仕事がありますか？それか興味ある分野とは？"
elif len(projects_hit_count) < 3:
a=len(projects_hit_count)
print "\nこんにちは、今のような募集がありますが、いかがですか？"
else:
a=3
print "\nこんにちは、今のような募集がありますが、いかがですか？"
for i in range(0,a):
sql="select id,company_id,title,description,location,keywords from projects where id ='%s'"%projects_hit_count[i][1]
# print sql
cursor.execute(sql)
result = cursor.fetchall()
for row in result:
print str(i+1)+"."
print str(row[2])
print str(row[5])
connector.commit()
cursor.close()
connector.close()
