Method of managing storage of user data
A method of managing storage of user data of a content recommendation system is provided. The content recommendation system comprises a user learning module for receiving data indicative of user actions, determining one or more learn actions based on the received data and storing the learn actions on a storage resource. The method comprises determining a parameter associated with aging out a learn action stored on a storage resource of a content recommendation system. The learn action determined based on data indicative of a user action. The method further comprises aging out the learn action stored on the storage resource based on the parameter.
1 . A method of managing storage of user data of a content recommendation system, the content recommendation system comprising a user learning module for receiving data indicative of user actions, determining one or more learn actions based on the received data and storing the learn actions on a storage resource, the method comprising:
determining a parameter associated with aging out a learn action stored on a storage resource of a content recommendation system, the learn action determined based on data indicative of a user action, the learn action comprising metadata of content selected by a user, wherein determining the parameter comprises monitoring a frequency of user actions and setting the parameter based on the monitored frequency; and
aging out the learn action stored on the storage resource based on the parameter, wherein aging out comprises modifying a decay function for assigning weights to a plurality of learn actions stored on the storage resource.
2 . The method of claim 1 , wherein the learn action comprises an indication that a user has viewed a content item for a specified period of time.
3 . The method of claim 1 , wherein the parameter is associated with aging out the learn action and additional data.
4 . The method of claim 3 , wherein the additional data comprises metadata associated with the content item.
5 . The method of claim 1 , wherein determining the parameter comprises monitoring a remaining storage capacity of the storage resource and setting the parameter based on the remaining storage capacity.
6 . The method of claim 1 , wherein the parameter comprises a number of learn actions stored on the storage resource.
7 . The method of claim 1 , wherein aging out comprises aging out the learn action based on the number of actions stored on the storage resource exceeding a threshold.
8 . The method of claim 1 , wherein aging out comprises deleting the learn action.
9 . The method of claim 1 , wherein modifying the decay function comprises altering a coefficient of the function associated with the learn action.
10 . The method of claim 1 , wherein the parameter is content type specific, content source specific, or user type specific.
11 . The method of claim 1 , wherein the content recommendation system comprises a content recommendation engine for providing a content item recommendations based on an actions of the user and content information concerning content available from one or more content sources.
12 . A non-transitory computer-readable medium having computer program code stored thereon, the program code executable by a processor to perform the method of claim 1 .
13 . The method of claim 1 , further comprising modifying the decay function comprises altering a coefficient of the function associated with the learn action to null or zero without deleting the learn action.
14 . The method of claim 1 , further comprising generating, in real-time upon receiving a content recommendation request from a user, a user profile using the decay function, the user profile for generating a content recommendation.
15 . A content recommendation system comprising a user learning module for receiving data indicative of user actions, determining one or more learn actions based on the received data and storing the learn actions on a storage resource, the user learning module for managing storage of user data of the content recommendation system, the learning module configured to:
determine a parameter associated with aging out a learn action stored on a storage resource of a content recommendation system, the learn action determined based on data indicative of a user action, the learn action comprising metadata of content selected by a user;
monitor a frequency of user actions and set the parameter based on the monitored frequency; and
age out the learn action stored on the storage resource based on the parameter, wherein the learning module is further configured to modify a decay function for assigning weights to a plurality of learn actions stored on the storage resource.
16 . The content recommendation system of claim 15 , wherein the learning module is further configured to:
monitor a frequency of user actions and set the parameter based on the monitored frequency.
17 . The content recommendation system of claim 15 , wherein the parameter comprises a content type specific parameter, a content source specific parameter, or a user type specific parameter.
18 . The content recommendation system of claim 17 , wherein the learning module is further configured to:
determine the content type parameter associated with aging out a learn action stored on the storage resource, the learn action determined based on data indicative of a user action with content of a specific content type.
19 . The content recommendation system of claim 17 , wherein the learning module is further configured to:
determine the content source parameter associated with aging out a learn action stored on the storage resource, the learn action determined based on data indicative of a user action with content from a specific content source.
20 . The content recommendation system of claim 17 , wherein the learning module is further configured to:
determine the user type parameter associated with aging out a learn action stored on the storage resource, the learn action determined based on data indicative of a user action by a specific user type.