Information providing method and system
Disclosed are an information providing method and system. In an embodiment, the method includes: acquiring product data and/or historical operation data; determining at least one feature description tag of an industrial product based upon the product data, and taking the at least one feature description tag of the industrial product as a feature of the industrial product; and/or determining at least one feature description tag of a user based upon the historical operation data, and taking the at least one feature description tag of the user as a feature of the user. The method further includes sending the feature of the industrial product and/or the feature of the user to a human-machine interactive device for display on a human-machine interactive interface. An embodiment further provides a reference suggestion for operative control of the industrial product by the user.
1 . An information providing method, comprising:
acquiring, via an edge computing device, product data of an industrial product and historical operation data of a user operating the industrial product, the historical operation data of the user including an operation log of the user;
determining, via the edge computing device, at least one feature description tag of the industrial product based upon the product data, and taking the at least one feature description tag of the industrial product as a feature of the industrial product;
determining, via the edge computing device, at least one feature description tag of the user based upon the historical operation data, and taking the at least one feature description tag of the user as a feature of the user;
sending, via the edge computing device, the feature of the industrial product and the feature of the user to a cloud platform;
determining, via the cloud platform, a recommended cloud function of the industrial product based upon the feature of the industrial product and the feature of the user by computing, via the cloud platform, a degree of interest of the user for each of multiple preset cloud functions, respectively, based upon the feature of the industrial product and the feature of the user and determining a cloud function, of the multiple preset cloud functions, with a degree of interest relatively higher than a third value, as the recommended cloud function; and
sending, via the edge computing device, the recommended cloud function and at least one of the feature of the industrial product or the feature of the user to a human-machine interactive device for display on a human-machine interactive interface of the human-machine interactive device,
wherein the degree of interest of the user for each respective cloud function of the multiple preset cloud functions is determined with a first formula, the first formula being
interest
1
=
μ
user
∑
k
=
1
N
P
user
,
k
*
q
k
,
Func
+
μ
product
∑
k
=
1
N
P
product
,
k
*
q
k
,
Func
wherein interest1 denotes the degree of interest of the user for the cloud function, μ user denotes a weighting value of a relationship between the user and the cloud function, N denotes a number of feature description tags of the cloud function, P user, k denotes a degree of correlation of the user for a kth feature description tag of the cloud function, q k, Func denotes a weighting value of the kth feature description tag of the cloud function, μ product denotes a weighting value of a relationship between the industrial product and the cloud function, and P product, k denotes a degree of correlation of the industrial product for the kth feature description tag of the cloud function.
2 . The method of claim 1 , wherein at least one of
the determining, via the edge computing device, the at least one feature description tag of the industrial product based upon the product data includes
extracting from the product data, via the edge computing device, a key field describing the industrial product,
computing a degree of similarity between the key field extracted and each of multiple preset product feature description tags, respectively, and
determining a product feature description tag, of the multiple preset product feature description tags, with a degree of similarity relatively higher than a first value as a feature description tag of the industrial product; or
the determining, via the edge computing device, the at least one feature description tag of the user based upon the historical operation data includes
extracting from the historical operation data, via the edge computing device, a key field describing the user,
computing a degree of similarity between the key field extracted and each of multiple preset user feature description tags, respectively, and
determining a user feature description tag, of the multiple preset user feature description tags, with a degree of similarity relatively higher than a second value as a feature description tag of the user.
3 . The method of claim 2 , wherein the determining, via the cloud platform, the recommended cloud function of the industrial product based upon the feature of the industrial product and the feature of the user, comprises:
subjecting, via the cloud platform, multiple preset cloud functions to collaborative filtering based upon the feature of the industrial product, to obtain at least one first cloud function;
subjecting the multiple preset cloud functions to the collaborative filtering based upon the feature of the user, to obtain at least one second cloud function; and
determining a joint cloud function of the at least one first cloud function and the at least one second cloud function as the recommended cloud function.
4 . The method of claim 2 , further comprising:
sending, via the edge computing device, the feature of the industrial product, the feature of the user and current operation information of the user for the industrial product to the cloud platform;
determining, via the cloud platform, a recommended operation of the user for the industrial product based upon the feature of the industrial product, the feature of the user and the current operation information; and
sending the recommended operation, via the edge computing device, to the human-machine interactive device for display on the human-machine interactive interface.
5 . The method of claim 4 , wherein the determining, via the cloud platform, of the recommended operation of the user for the industrial product based upon the feature of the industrial product, the feature of the user and the current operation information comprises:
computing, via the cloud platform, a degree of interest of the user for each of multiple preset historical operations, respectively, based upon the feature of the industrial product, the feature of the user and the current operation information, and
determining a historical operation, of the multiple preset historical operations, with a degree of interest relatively higher than a fourth value as the recommended operation.
6 . The method of claim 5 , wherein the cloud platform is configured to use a second formula to compute the degree of interest of the user for each historical operation, the second formula comprising:
interest
2
=
μ
.
user
∑
K
=
1
M
P
.
user
,
k
*
q
.
k
,
Operation
+
μ
.
product
∑
K
=
1
M
P
.
product
,
k
*
q
.
k
,
Operation
wherein interest2 denotes the degree of interest of the user for the historical operation;
{dot over (μ)} user denotes a weighting value of a relationship between the user and the historical operation;
{dot over (P)} user, k denotes a degree of correlation of the user for a kth feature description tag of the historical operation;
{dot over (q)} k, Operation denotes a weighting value of the kth feature description tag of the historical operation;
{dot over (μ)} product denotes a weighting value of a relationship between the industrial product and the historical operation;
{dot over (P)} product, k denotes a degree of correlation of the industrial product for the kth feature description tag of the historical operation; and
M is a number of feature description tags of the historical operation.
7 . The method of claim 1 , wherein the determining, via the cloud platform, the recommended cloud function of the industrial product based upon the feature of the industrial product and the feature of the user, comprises:
subjecting, via the cloud platform, multiple preset cloud functions to collaborative filtering based upon the feature of the industrial product, to obtain at least one first cloud function;
subjecting multiple preset cloud functions to collaborative filtering based upon the feature of the user, to obtain at least one second cloud function; and
determining a joint cloud function of the at least one first cloud function and the at least one second cloud function as the recommended cloud function.
8 . The method of claim 1 , further comprising:
sending, via the edge computing device, the feature of the industrial product, the feature of the user and current operation information of the user for the industrial product to a cloud platform;
determining, via the cloud platform, a recommended operation of the user for the industrial product based upon the feature of the industrial product, the feature of the user and the current operation information; and
sending the recommended operation, via the edge computing device, to the human-machine interactive device for display on the human-machine interactive interface.
9 . The method of claim 8 , wherein the determining, via the cloud platform, of the recommended operation of the user for the industrial product based upon the feature of the industrial product, the feature of the user and the current operation information comprises:
computing, via the cloud platform, a degree of interest of the user for each of multiple preset historical operations, respectively, based upon the feature of the industrial product, the feature of the user and the current operation information, and
determining a historical operation, of the multiple preset historical operations, with a degree of interest relatively higher than a fourth value as the recommended operation.
10 . The method of claim 9 , wherein the cloud platform is configured to use a second formula to compute the degree of interest of the user for each historical operation, the second formula comprising:
interest
2
=
μ
.
user
∑
K
=
1
M
P
.
user
,
k
*
q
.
k
,
Operation
+
μ
.
product
∑
K
=
1
M
P
.
product
,
k
*
q
.
k
,
Operation
wherein interest2 denotes the degree of interest of the user for the historical operation;
{dot over (μ)} user denotes a weighting value of a relationship between the user and the historical operation;
{dot over (P)} user, k denotes a degree of correlation of the user for a kth feature description tag of the historical operation;
{dot over (q)} k, Operation denotes a weighting value of the kth feature description tag of the historical operation;
{dot over (μ)} product denotes a weighting value of a relationship between the industrial product and the historical operation;
{dot over (P)} product, k denotes a degree of correlation of the industrial product for the kth feature description tag of the historical operation; and
M is a number of feature description tags of the historical operation.
11 . An information providing system, comprising:
a human-machine interactive device;
an industrial product; and
an edge computing device, connected to the human-machine interactive device and the industrial product, configured to
acquire product data of the industrial product and historical operation data of a user operating the industrial product, the historical operation data of the user including an operation log of the user,
determine at least one feature description tag of the industrial product based upon the product data, and take the at least one feature description tag of the industrial product determined as a feature of the industrial product,
determine at least one feature description tag of the user based upon the historical operation data, and take the at least one feature description tag of the user as a feature of the user,
send the feature of the industrial product and the feature of the user to a cloud platform to determine a recommended cloud function of the industrial product based upon the feature of the industrial product and the feature of the user by computing, via the cloud platform, a degree of interest of the user for each of multiple preset cloud functions, respectively, based upon the feature of the industrial product and the feature of the user and determining a cloud function, of the multiple preset cloud functions, with a degree of interest relatively higher than a third value, as the recommended cloud function; and
send the recommended cloud function and at least one of the feature of the industrial product or the feature of the user to the human-machine interactive device, for display on a human-machine interactive interface of the human-machine interactive device,
wherein the degree of interest of the user for each respective cloud function of the multiple preset cloud functions is determined with a first formula, the first formula being
interest
1
=
μ
user
∑
k
=
1
N
P
user
,
k
*
q
k
,
Func
+
μ
product
∑
k
=
1
N
P
product
,
k
*
q
k
,
Func
wherein interest1 denotes the degree of interest of the user for the cloud function, μ user denotes a weighting value of a relationship between the user and the cloud function, N denotes a number of feature description tags of the cloud function, P user, k denotes a degree of correlation of the user for a kth feature description tag of the cloud function, q k, Func denotes a weighting value of the kth feature description tag of the cloud function, μ product denotes a weighting value of a relationship between the industrial product and the cloud function, and P product, k denotes a degree of correlation of the industrial product for the kth feature description tag of the cloud function.