US2015051974A1PendingUtilityA1
Recommendation of network object information to user
Est. expiryApr 13, 2029(~2.7 yrs left)· nominal 20-yr term from priority
G06F 16/9535G06Q 30/0255H04L 67/10G06Q 30/02
52
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Claims
Abstract
Recommending network object information to a user includes, for each of a plurality of network objects, a respective plurality of behavior frequencies by the user is determined; a network object among the plurality of network objects that is of interest to the user is identified, the identification being based at least in part on the respective plurality of behavior frequencies that corresponds to each of the plurality of network objects; and additional information relating to the identified network object is provided to the user.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . (canceled)
2 . A system, comprising:
a deriver to determine, for each of a plurality of network objects, a respective plurality of behavior frequencies by a user; a selector to identify one or more network objects among the plurality of network objects that are of interest to the user, the identification being based at least in part on the respective plurality of behavior frequencies that corresponds to each of the plurality of network objects, wherein to identify the one or more network objects includes to:
determine a degree of user preference for each of at least a subset of the plurality of network objects;
select a first network object of the plurality of network objects based at least in part on a degree of user preference associated with the first network object;
select a second network object of the plurality of network objects based at least in part on a degree of user preference associated with the second network object; and
combine the first network object and the second network object into a combined network object; and
a provider to provide to the user recommended product information relating to the combined network object.
3 . The system of claim 2 , wherein the plurality of behaviors includes releasing information on one of the plurality of network objects.
4 . The system of claim 2 , wherein the plurality of behaviors includes receiving an e-mail containing information on one of the plurality of network objects.
5 . The system of claim 2 , wherein the plurality of behaviors includes releasing opinion information on one of the plurality of network objects.
6 . The system of claim 2 , wherein the plurality of behaviors includes retrieving information on one of the plurality of network objects.
7 . The system of claim 2 , wherein the plurality of behaviors includes searching for information on one of the plurality of network objects.
8 . The system of claim 2 , wherein to determine the degree of user preference for each of the at least subset of the plurality of network objects comprises to:
derive, for each of the at least subset of the plurality of network objects, a respective sum of the respective plurality of behavior frequencies by the user, wherein the respective sum comprises adding together each of the respective plurality of behavior frequencies.
9 . The system of claim 2 , wherein to determine the degree of user preference for each of the at least subset of the plurality of network objects comprises to:
assign each of the respective plurality of behavior frequencies a respective weight; and derive, for each of the at least subset of the plurality of network objects, a respective sum of the respective weighted plurality of behavior frequencies by the user, wherein the respective sum comprises adding together each of the respective weighted plurality of behavior frequencies.
10 . The system of claim 9 , wherein the respective weight comprises a value between 0 and 1.
11 . The system of claim 9 , wherein to derive, for each of the at least subset of the plurality of network objects, a respective sum of the respective weighted plurality of behavior frequencies by the user is derived by equation:
P
(
K
1
)
=
∑
j
=
1
T
∑
i
=
1
n
Cnt
(
Act
(
i
)
,
Time
(
j
)
,
K
1
)
×
twc
(
Act
(
i
)
)
×
tdf
(
Time
(
j
)
)
;
wherein:
P(K 1 ) denotes the respective sum of the respective weighted plurality of behavior frequencies associated with a network object K 1 among the plurality of network objects;
Cnt(Act (i),Time(j), K 1 ) denotes a behavior frequency that an i th network behavior Act(i) among the plurality of behavior frequencies is performed on the network object K 1 in a j th period of time Time(j);
twc(Act(i)) denotes an assigned weight of the i th network behavior Act(i);
tdf(Time(j)) denotes the assigned weight of the i th network behavior Act(i) performed in the j th period of time Time(j);
n denotes a number of the plurality of network behaviors; and
T denotes a number of evaluated periods of time.
12 . A method, comprising:
determining, using a processor, for each of a plurality of network objects, a respective plurality of behavior frequencies by a user; identifying one or more network objects among the plurality of network objects that are of interest to the user, the identification being based at least in part on the respective plurality of behavior frequencies that corresponds to each of the plurality of network objects, wherein identifying the one or more network objects includes:
determining a degree of user preference for each of at least a subset of the plurality of network objects;
selecting a first network object of the plurality of network objects based at least in part on a degree of user preference associated with the first network object;
selecting a second network object of the plurality of network objects based at least in part on a degree of user preference associated with the second network object; and
combining the first network object and the second network object into a combined network object; and
providing to the user recommended product information relating to the combined network object.
13 . The method of claim 12 , wherein the plurality of behaviors includes releasing information on one of the plurality of network objects.
14 . The method of claim 12 , wherein the plurality of behaviors includes receiving an e-mail containing information on one of the plurality of network objects.
15 . The method of claim 12 , wherein the plurality of behaviors includes releasing opinion information on one of the plurality of network objects.
16 . The method of claim 12 , wherein the plurality of behaviors includes retrieving information on one of the plurality of network objects.
17 . The method of claim 12 , wherein the plurality of behaviors includes searching for information on one of the plurality of network objects.
18 . The method of claim 12 , wherein determining the degree of user preference for each of the at least subset of the plurality of network objects comprises:
deriving, for each of the at least subset of the plurality of network objects, a respective sum of the respective plurality of behavior frequencies by the user, wherein the respective sum comprises adding together each of the respective plurality of behavior frequencies.
19 . The method of claim 12 , wherein determining the degree of user preference for each of the at least subset of the plurality of network objects comprises:
assigning each of the respective plurality of behavior frequencies a respective weight; and deriving, for each of the at least subset of the plurality of network objects, a respective sum of the respective weighted plurality of behavior frequencies by the user, wherein the respective sum comprises adding together each of the respective weighted plurality of behavior frequencies.
20 . The method of claim 19 , wherein the respective weight comprises a value between 0 and 1.
21 . The method of claim 19 , wherein deriving, for each of the at least subset of the plurality of network objects, a respective sum of the respective weighted plurality of behavior frequencies by the user is derived by equation:
P
(
K
1
)
=
∑
j
=
1
T
∑
i
=
1
n
Cnt
(
Act
(
i
)
,
Time
(
j
)
,
K
1
)
×
twc
(
Act
(
i
)
)
×
tdf
(
Time
(
j
)
)
;
wherein:
P(K 1 ) denotes the respective sum of the respective weighted plurality of behavior frequencies associated with a network object K 1 among the plurality of network objects;
Cnt(Act(i),Time(j),K 1 ) denotes a behavior frequency that an i th network behavior Act(i) among the plurality of behavior frequencies is performed on the network object K 1 in a j th period of time Time(j);
twc (Act(i)) denotes an assigned weight of the i th network behavior Act(i);
tdf (Time(j)) denotes the assigned weight of the i th network behavior Act(i) performed in the j th period of time Time(j);
n denotes a number of the plurality of network behaviors; and
T denotes a number of evaluated periods of time.
22 . A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
determining for each of a plurality of network objects, a respective plurality of behavior frequencies by a user; identifying one or more network objects among the plurality of network objects that are of interest to the user, the identification being based at least in part on the respective plurality of behavior frequencies that corresponds to each of the plurality of network objects, wherein identifying the one or more network objects includes:
determining a degree of user preference for each of at least a subset of the plurality of network objects;
selecting a first network object of the plurality of network objects based at least in part on a degree of user preference associated with the first network object;
selecting a second network object of the plurality of network objects based at least in part on a degree of user preference associated with the second network object; and
combining the first network object and the second network object into a combined network object; and
providing to the user recommended product information relating to the combined network object.Join the waitlist — get patent alerts
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