def cut():
value = {}
users = get_user_by_group(100022)
posts, post_relation, comments, comment_relation = user_comment_smilar(users)
for user in users:
user_comments = comment_by_group_user(100022, user)
user_comment = np.zeros(len(posts), np.float)
user_comment_length = len(user_comments)
for comment in user_comments:
comment_index = comments.index(comment.id)
user_comment += comment_relation[comment_index]
user_comment = np.dot(user_comment, post_relation)
if user_comment_length:
user_comment = user_comment/user_comment_length
user_comment = zip(user_comment, posts)
user_comment.sort(key=lambda x:x[0], reverse=True)
_ = []
res = []
for p in posts_by_users([user]):
_.append(p.id)
print _
for i in user_comment:
print i[0], '!!'
if i[0] not in _:
res.append(i)
print res
length = int(len(res)*0.2)
res = res[:length][::-1]
value[user] = res
from tofromfile import tofile
tofile('re_recommend', value)
def main():
value = {}
users = get_user_by_group(100022)
posts, post_relation, comments, comment_relation = user_comment_smilar(users)
print len(users), users
for user in users:
user_comments = comment_by_group_user(100022, user)
user_comment = np.zeros(len(posts), np.float)
user_comment_length = len(user_comments)
for comment in user_comments:
comment_index = comments.index(comment.id)
user_comment += comment_relation[comment_index]
user_comment = np.dot(user_comment, post_relation)
if user_comment_length:
user_comment = user_comment/user_comment_length
user_comment = zip(user_comment, posts)
user_comment.sort(key=lambda x:x[0], reverse=True)
value[user] = user_comment
print 'to_file!!', value
from tofromfile import tofile
tofile('recommend', value)
if __name__ == '__main__':
posts, post_relation, comments, comment_relation = get_similar_post_comment()
print posts, post_relation
print comments, comment_relation
value = {}
for user in User.where():
print user.name.encode('U8')
cs = get_comment_by_user_id(user.id)
_ = np.zeros(len(posts), np.float)
l = 0
for c in cs:
c_index = comments.index(c.id)
_ += comment_relation[c_index]
l += 1
_ = np.dot(_, post_relation)
if l:
_ = _/l
_ = zip(_, posts)
_.sort(key = lambda x:x[0], reverse=True)
value[user.id] = _
for i,j in cut_tail(_):
print 'http://social-blogger.tk/post/%s'%j
from tofromfile import tofile
tofile('recommend', value)
def tofile(self, f):
tofile(
f, (self._count, self.idf())
)
def tofile(self, f):
tofile(f, (self._count, self.idf()))
