User profile based on clustering tiered descriptors

Patent metadata

Field	Value
Publication number	US-2019050488-A1
Application number	US-201816161887-A
Country	US
Kind code	A1
Filing date	Oct 16, 2018
Priority date	Sep 12, 2012
Publication date	Feb 14, 2019
Grant date	—

Abstract

Methods, apparatus, systems, and articles of manufacture are disclosed that involve a user profile based on clustering tiered descriptors. An example method includes grouping descriptors into a cluster of descriptors based on an association between the descriptors and each of a first item and a second item, accessing, via a user device, biometric data of a user, determining a first activity in which the user is engaged based on contextual data that correlates the cluster of descriptors with the biometric data of the user received from the user device via the network, generating a user profile based on the first activity of the user and the cluster of descriptors, and generating, in response to a second activity of the user matching the first activity associated with the cluster of descriptors within the user profile, a recommendation including a third item based on the user profile.

First claim

What is claimed is:

1 . An apparatus comprising:
a cluster module to group descriptors into a cluster of descriptors based on an association between the descriptors and each of a first item and a second item; a context module to access, via a user device communicatively coupled to the context module via a network, biometric data of a user; a correlation module to determine a first activity in which the user is engaged based on contextual data that correlates the cluster of descriptors with the biometric data of the user received from the user device via the network; a profile module to generate a user profile based on the first activity of the user and the cluster of descriptors; and a recommender to, in response to a second activity of the user matching the first activity associated with the cluster of descriptors within the user profile, generate a recommendation including a third item based on the user profile, at least one of the cluster module, the context module, the correlation module, or the recommender is implemented by one or more hardware processors.

2 . The apparatus of claim 1 , wherein:
the first item and the second item are included in a collection of items associated with the user; the collection of items is a media library of the user; the first item is a first media file in the media library of the user; and the second item is a second media file in the media library of the user.

3 . The apparatus of claim 1 , wherein:
the correlation module is further to determine the first activity of the user based on contextual data that correlates the first item and the second item with a first and second location of the user, the locations received from the user device via the network; and the profile module is further to store a name of the group within the user profile as corresponding to the first activity determined based on the first and second location of the user.

4 . The apparatus of claim 3 , wherein:
the correlation module is further to, when the first location is associated with a neighborhood associated with the user and the second location is associated with a business district, determine the first activity of the user is commuting; and the profile module is further to store the name of the group within the user profile as corresponding to commuting.

5 . The apparatus of claim 1 , wherein:
the correlation module is further to determine the first activity of the user based on contextual data that correlates the first item and the second item with a day of week and a time of day; and the profile module is further to store a name of the group within the user profile as corresponding to the first activity determined based on the day of week and the time of day.

6 . The apparatus of claim 1 , wherein:
the correlation module is further to determine the first activity of the user based on contextual data that correlates the first item and the second item with an appointment of the user, the appointment retrieved from calendar data associated with the user; and the profile module is further to store a name of the group within the user profile as corresponding to the first activity determined based on the appointment.

7 . The apparatus of claim 1 , wherein:
the correlation module is further to determine an anomalous phase of the user based on contextual data that correlates the first item and the second item with a time period that has a duration shorter than a threshold duration; and the profile module is further to omit a name of the group from the user profile when the anomalous phase of the user is determined.

8 . A non-transitory machine-readable storage medium comprising instructions that, when executed, cause at least one processor to at least:
group descriptors into a cluster of descriptors based on an association between the descriptors and each of a first item and a second item; access, via a user device communicatively coupled to the machine via a network, biometric data of a user; determine a first activity in which the user is engaged based on contextual data that correlates the cluster of descriptors with the biometric data of the user received from the user device via the network; generate a user profile based on the first activity of the user and the cluster of descriptors; and when a second activity of the user matches the first activity associated with the cluster of descriptors within the user profile, generate a recommendation including a third item based on the user profile.

9 . The non-transitory machine-readable storage medium of claim 8 , wherein:
the first item and the second item are specimens of a collection of items that belong to the user. the collection of items is a media library of the user; the first item is a first media file in the media library of the user; and the second item is a second media file in the media library of the user.

10 . The non-transitory machine-readable storage medium of claim 8 , wherein the instructions, when executed, further cause the at least one processor to:
determine the first activity of the user based on contextual data that correlates the first item and the second item with a day of week and a time of day; and store a name of the group within the user profile as corresponding to the first activity determined based on the day of week and the time of day.

11 . The non-transitory machine-readable storage medium of claim 8 , wherein the instructions, when executed, further cause the at least one processor to:
determine the first activity of the user based on contextual data that correlates the first item and the second item with a first and second location of the user, the locations received from the user device via the network; and store a name of the group within the user profile as corresponding to the first activity determined based on the first and second location of the user.

12 . The non-transitory machine-readable storage medium of claim 8 , wherein the instructions, when executed, further cause the at least one processor to:
determine the first activity of the user based on contextual data that correlates the first item and the second item with an appointment of the user, the appointment retrieved from calendar data associated with the user; and store a name of the group within the user profile as corresponding to the first activity determined based on the appointment.

13 . The non-transitory machine-readable storage medium of claim 8 , wherein the instructions, when executed, further cause the at least one processor to:
determine an anomalous phase of the user based on contextual data that correlates the first item and the second item with a time period that has a duration shorter than a threshold duration; and when the anomalous phase of the user is determined, omit a name of the group from the user profile.

14 . A method comprising:
grouping, by executing an instruction with a processor, descriptors into a cluster of descriptors based on an association between the descriptors and each of a first item and a second item; accessing, via a user device communicatively coupled to the processor via a network, biometric data of a user; determining, by executing an instruction the processor, a first activity in which the user is engaged based on contextual data that correlates the cluster of descriptors with the biometric data of the user received from the user device via the network; generating, by executing an instruction the processor, a user profile based on the first activity of the user and the cluster of descriptors; and generating, by executing an instruction the pr

Assignees

• Gracenote Inc

Inventors

• Popp Phillip
• Chen Ching-Wei
• Dimaria Peter C
• Cremer Markus K

Classifications

• G06F16/636

  by using biological or physiological data · CPC title

• G06F16/9535 Primary

  Search customisation based on user profiles and personalisation · CPC title

• G06F16/68

  Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually · CPC title

• G06F17/30867 Primary

  Physics · mapped topic

• G06F17/30764

  Physics · mapped topic