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alpha
physical
Commits
e3387b7b
Commit
e3387b7b
authored
Mar 29, 2019
by
段英荣
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Merge branch 'master' into 'test'
Master See merge request
!216
parents
0ad7f0ca
cf209f71
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Showing
5 changed files
with
70 additions
and
36 deletions
+70
-36
collect_data.py
linucb/views/collect_data.py
+4
-3
linucb.py
linucb/views/linucb.py
+10
-9
topic.py
search/utils/topic.py
+44
-19
topic.py
search/views/topic.py
+10
-4
user_extra.py
trans2es/models/user_extra.py
+2
-1
No files found.
linucb/views/collect_data.py
View file @
e3387b7b
...
...
@@ -47,18 +47,19 @@ class CollectData(object):
def
update_recommend_tag_list
(
self
,
device_id
,
user_feature
=
None
):
try
:
recommend_tag_list
=
list
()
recommend_tag_dict
=
dict
()
redis_linucb_tag_data_dict
=
self
.
_get_user_linucb_info
(
device_id
)
if
len
(
redis_linucb_tag_data_dict
)
==
0
:
recommend_tag_list
=
LinUCB
.
get_default_tag_list
()
LinUCB
.
init_device_id_linucb_info
(
redis_client
,
self
.
linucb_matrix_redis_prefix
,
device_id
,
recommend_tag_list
)
else
:
user_feature
=
user_feature
if
user_feature
else
self
.
user_feature
recommend_tag_
lis
t
=
LinUCB
.
linucb_recommend_tag
(
device_id
,
redis_linucb_tag_data_dict
,
user_feature
,
list
(
redis_linucb_tag_data_dict
.
keys
()))
recommend_tag_
dic
t
=
LinUCB
.
linucb_recommend_tag
(
device_id
,
redis_linucb_tag_data_dict
,
user_feature
,
list
(
redis_linucb_tag_data_dict
.
keys
()))
logging
.
info
(
"duan add,device_id:
%
s,recommend_tag_list:
%
s"
%
(
str
(
device_id
),
str
(
recommend_tag_list
)))
if
len
(
recommend_tag_
lis
t
)
>
0
:
if
len
(
recommend_tag_
dic
t
)
>
0
:
tag_recommend_redis_key
=
self
.
linucb_recommend_redis_prefix
+
str
(
device_id
)
redis_client
.
set
(
tag_recommend_redis_key
,
json
.
dumps
(
recommend_tag_list
))
redis_client
.
set
(
tag_recommend_redis_key
,
json
.
dumps
(
list
(
recommend_tag_dict
.
keys
())
))
# Todo:设置过期时间,调研set是否支持
redis_client
.
expire
(
tag_recommend_redis_key
,
7
*
24
*
60
*
60
)
...
...
linucb/views/linucb.py
View file @
e3387b7b
...
...
@@ -14,9 +14,9 @@ from django.conf import settings
class
LinUCB
:
d
=
2
alpha
=
0.
25
r1
=
1
r0
=
-
0.
5
alpha
=
0.
1
r1
=
1
0
r0
=
-
0.
1
default_tag_list
=
list
()
@classmethod
...
...
@@ -70,7 +70,7 @@ class LinUCB:
#art_max = tag_list[np.argmax(np.dot(xaT, theta_tmp) + cls.alpha * np.sqrt(np.dot(np.dot(xaT, AaI_tmp), xa)))]
top_tag_
set
=
se
t
()
top_tag_
dict
=
dic
t
()
np_score_list
=
list
()
np_score_dict
=
dict
()
...
...
@@ -85,18 +85,19 @@ class LinUCB:
sorted_np_score_list
=
sorted
(
np_score_list
,
reverse
=
True
)
for
top_score
in
sorted_np_score_list
:
for
top_score_index
in
np_score_dict
[
top_score
]:
top_tag_set
.
add
(
str
(
tag_list
[
top_score_index
],
encoding
=
"utf-8"
))
if
len
(
top_tag_set
)
>=
10
:
tag_id
=
str
(
tag_list
[
top_score_index
],
encoding
=
"utf-8"
)
top_tag_dict
[
tag_id
]
=
top_score
if
len
(
top_tag_dict
)
>=
10
:
break
if
len
(
top_tag_
se
t
)
>=
10
:
if
len
(
top_tag_
dic
t
)
>=
10
:
break
logging
.
info
(
"duan add,device_id:
%
s,sorted_np_score_list:
%
s,np_score_dict:
%
s"
%
(
str
(
device_id
),
str
(
sorted_np_score_list
),
str
(
np_score_dict
)))
return
list
(
top_tag_set
)
return
top_tag_dict
except
:
logging
.
error
(
"catch exception,err_msg:
%
s"
%
traceback
.
format_exc
())
return
[]
return
{}
@classmethod
def
init_device_id_linucb_info
(
cls
,
redis_cli
,
redis_prefix
,
device_id
,
tag_list
):
...
...
search/utils/topic.py
View file @
e3387b7b
...
...
@@ -134,7 +134,7 @@ class TopicUtils(object):
"""
try
:
attention_user_id_list
=
list
()
pick_user_id_list
=
list
()
#
pick_user_id_list = list()
# same_group_id_list = list()
user_tag_list
=
list
()
...
...
@@ -145,8 +145,8 @@ class TopicUtils(object):
attention_user_info_list
=
result_dict
[
"hits"
][
0
][
"_source"
][
"attention_user_id_list"
]
attention_user_id_list
=
[
item
[
"user_id"
]
for
item
in
attention_user_info_list
]
pick_user_info_list
=
result_dict
[
"hits"
][
0
][
"_source"
][
"pick_user_id_list"
]
pick_user_id_list
=
[
item
[
"user_id"
]
for
item
in
pick_user_info_list
]
#
pick_user_info_list = result_dict["hits"][0]["_source"]["pick_user_id_list"]
#
pick_user_id_list = [item["user_id"] for item in pick_user_info_list]
# same_pictorial_user_info_list = result_dict["hits"][0]["_source"]["same_pictorial_user_id_list"]
#
...
...
@@ -165,22 +165,22 @@ class TopicUtils(object):
"language_type"
:
1
}
},
"weight"
:
3
"weight"
:
4
},
{
"
linear
"
:
{
"
gauss
"
:
{
"create_time"
:
{
"scale"
:
"1d"
,
"decay"
:
0.99
}
},
"weight"
:
5
00
"weight"
:
5
}
]
if
len
(
user_similar_score_list
)
>
0
:
for
item
in
user_similar_score_list
[:
100
]:
score_item
=
3
*
10
*
item
[
1
]
score_item
=
2
+
item
[
1
]
functions_list
.
append
(
{
"filter"
:
{
"bool"
:
{
...
...
@@ -197,14 +197,14 @@ class TopicUtils(object):
"weight"
:
3
,
}
)
if
len
(
pick_user_id_list
)
>
0
:
functions_list
.
append
(
{
"filter"
:
{
"bool"
:
{
"should"
:
{
"terms"
:
{
"user_id"
:
pick_user_id_list
}}}},
"weight"
:
2
}
)
#
if len(pick_user_id_list) > 0:
#
functions_list.append(
#
{
#
"filter": {"bool": {
#
"should": {"terms": {"user_id": pick_user_id_list}}}},
#
"weight": 2
#
}
#
)
# if len(same_pictorial_id_list) > 0:
# functions_list.append(
...
...
@@ -224,15 +224,34 @@ class TopicUtils(object):
"weight"
:
1
}
)
if
len
(
recommend_tag_list
)
>
0
:
if
len
(
recommend_tag_list
)
>
0
:
if
len
(
recommend_tag_list
)
>
1
:
functions_list
+=
[
{
"filter"
:
{
"term"
:
{
"tag_list"
:
recommend_tag_list
[
0
]}},
"weight"
:
4
},
{
"filter"
:
{
"terms"
:
{
"tag_list"
:
recommend_tag_list
[
1
:]}},
"weight"
:
3
}
]
else
:
functions_list
.
append
(
{
"filter"
:
{
"bool"
:
{
"should"
:
{
"terms"
:
{
"edit_tag_list"
:
recommend_tag_list
}}}},
"filter"
:
{
"terms"
:
{
"tag_list"
:
recommend_tag_list
}},
"weight"
:
3
}
)
# for tag_id in recommend_tag_dict:
# functions_list.append(
# {
# "filter": {"term": {"tag_list": tag_id}},
# "weight": recommend_tag_dict[tag_id]
# }
# )
low_content_level
=
4
if
query_type
==
TopicPageType
.
FIND_PAGE
else
3
query_function_score
=
{
"query"
:
{
...
...
@@ -319,7 +338,13 @@ class TopicUtils(object):
},
"order"
:
"desc"
}
}
},
# {
# "offline_score":{
# "order": "desc"
# }
# },
"_score"
]
result_dict
=
ESPerform
.
get_search_results
(
ESPerform
.
get_cli
(),
sub_index_name
=
index_type
,
query_body
=
q
,
offset
=
offset
,
size
=
size
)
...
...
search/views/topic.py
View file @
e3387b7b
...
...
@@ -57,7 +57,13 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
tag_recommend_redis_key
=
"physical:linucb:tag_recommend:device_id:"
+
str
(
device_id
)
recommend_tag_list
=
[]
# recommend_tag_dict = dict()
# tag_recommend_val = redis_client.get(tag_recommend_redis_key)
# if tag_recommend_val:
# recommend_tag_dict = json.loads(str(tag_recommend_val, encoding="utf-8"))
recommend_tag_list
=
list
()
tag_recommend_val
=
redis_client
.
get
(
tag_recommend_redis_key
)
if
tag_recommend_val
:
recommend_tag_list
=
json
.
loads
(
str
(
tag_recommend_val
,
encoding
=
"utf-8"
))
...
...
@@ -123,15 +129,15 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
# break
have_read_topic_id_list
.
extend
(
topic_id_list
)
if
len
(
have_read_topic_id_list
)
>
5
000
:
cut_len
=
len
(
have_read_topic_id_list
)
-
5
000
if
len
(
have_read_topic_id_list
)
>
30
000
:
cut_len
=
len
(
have_read_topic_id_list
)
-
30
000
have_read_topic_id_list
=
have_read_topic_id_list
[
cut_len
:]
redis_dict
=
{
"have_read_topic_list"
:
json
.
dumps
(
have_read_topic_id_list
),
}
redis_client
.
hmset
(
redis_key
,
redis_dict
)
# 每个session key保存15分钟
redis_client
.
expire
(
redis_key
,
60
*
60
*
24
*
3
)
redis_client
.
expire
(
redis_key
,
60
*
60
*
24
*
3
0
)
return
topic_id_list
except
:
...
...
trans2es/models/user_extra.py
View file @
e3387b7b
...
...
@@ -15,7 +15,8 @@ class UserExtra(models.Model):
db_table
=
"user_extra"
id
=
models
.
IntegerField
(
verbose_name
=
"主键ID"
,
primary_key
=
True
)
user_id
=
models
.
BigIntegerField
(
verbose_name
=
u"用户ID"
)
user_id
=
models
.
CharField
(
verbose_name
=
u"用户ID"
,
max_length
=
100
)
is_shadow
=
models
.
BooleanField
(
verbose_name
=
u"是否是马甲账户"
)
is_online
=
models
.
BooleanField
(
verbose_name
=
u"是否上线"
)
is_recommend
=
models
.
BooleanField
(
verbose_name
=
u"是否推荐"
)
...
...
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