SYSTEMS AND METHODS FOR AUTOMATIC PROGRAM RECOMMENDATIONS BASED ON USER INTERACTIONS

• US 20150254333A1
• Filed: 05/19/2015
• Published: 09/10/2015
• Est. Priority Date: 09/25/2012
• Status: Active Grant

• Current Assignee: Rovi Guides, Inc. (Adeia Inc.)
• Original Assignee: Rovi Guides, Inc. (Adeia Inc.)
• Inventors: Fife, Brian, Braness, Jason, Papish, Michael, Woods, Thomas Steven
• Granted Patent: US 9,298,810 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3334 Selection or weighting of terms from queries, including natural language queries
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/74 Browsing; Visualisation therefor end-user interfaces for requesting or interacting with video content, e.g. video on demand interfaces or electronic program guides, H04N21/472
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G10L 17/22 Interactive procedures; Man-machine interfaces
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/41265 having a remote control device for bidirectional communication between the remote control device and client device unidirectional remote control device H04N21/42204
• CPC Class Codes: H04N 21/442 Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk arrangements for monitoring broadcast services or broadcast-related services H04H60/29; arrangements for identifying or recognising characteristics with a direct linkage to broadcast information H04H60/35; monitoring of user activities for profile generation for accessing a video database G06F16/739; monitoring in wireless networks H04W24/00
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/4667 Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/47214 for content reservation or setting reminders; for requesting event notification, e.g. of sport results or stock market stock exchange data over packet-switching network H04L12/1804; push services over packet-switching network H04L12/1859; notification of incoming messages in packet switching networks H04L51/224
• CPC Class Codes: H04N 21/4826 using recommendation lists, e.g. of programs or channels sorted out according to their score

Abstract

Methods and systems are provided for generating automatic program recommendations based on user interactions. In some embodiments, control circuitry processes verbal data received during an interaction between a user of a user device and a person with whom the user is interacting. The control circuitry analyzes the verbal data to automatically identify a media asset referred to during the interaction by at least one of the user and the person with whom the user is interacting. The control circuitry adds the identified media asset to a list of media assets associated with the user of the user device. The list of media assets is transmitted to a second user device of the user.

Claims

1-33. -33. (canceled)

34. A method for automatically recommending a media asset based on an interaction, the method comprising:

processing, by control circuitry, verbal data from an interaction between a user and a person with whom the user is interacting;

cross-referencing the processed data with a media asset database to identify a media asset referred to during the interaction;

identifying the person with whom the user is interacting based on the processed data;

retrieving, from a database of friends of the user, a recommendation weight corresponding to the identity of the person with whom the user is interacting; and

determining whether to add the identified media asset to a list of media assets associated with the user based on the retrieved recommendation weight corresponding to the identity of the person with whom the user is interacting.

35. The method of claim 34, further comprising, in response to determining that the identified media asset should be added to the list of media assets, adding the identified media asset to the list of media assets associated with the user by adding the identified media asset to a list or queue of media assets to be transmitted to the user, adding the identified media asset to a list of media assets recommended to the user, creating a bookmark to the identified media asset, creating a link to the identified media asset, or scheduling a recording of the identified media asset on a device associated with the user.

37. The method of claim 34, further comprising:

monitoring a number of times that the identified media asset was identified within the verbal data;

comparing the number of times that the identified media asset was identified to a threshold number, and

in response to the number of times the identified media asset was identified exceeding the threshold number, adding the identified media asset to the list of media assets associated with the user.

38. The method of claim 34, further comprising:

monitoring a number of interactions in which the identified media asset was identified;

comparing the number of interactions in which the identified media asset was identified to a threshold number; and

in response to the number of interactions in which the identified media asset was identified exceeding the threshold number, adding the identified media asset to the list of media assets associated with the user.

39. The method of claim 34, further comprising:

determining a plurality of candidate media assets based on a profile associated with at least one of the user and the person with whom the user is interacting; and

identifying, from the determined list of candidate media assets, a media asset referred to during the interaction by at least one of the user and the person with whom the user is interacting.

40. The method of claim 34, further comprising:

receiving a user input corresponding to the person with whom the user is interacting;

modifying, based on the received user input, the recommendation weight corresponding to the identity of the person with whom the user is interacting; and

storing the modified recommendation weight in the database of friends of the user.

41. The method of claim 40, wherein the user input indicates favoring the person with whom the user is interacting, and modifying the recommendation weight further comprises increasing the recommendation weight.

42. The method of claim 40, wherein the user input indicates ignoring the person with whom the user is interacting, and modifying the recommendation weight further comprises decreasing the recommendation weight.

43. The method of claim 34, wherein the database of friends of the user receives information from at least one of the user'"'"'s social network contacts, the user'"'"'s mobile device contacts, the user'"'"'s email contacts, and the user'"'"'s messaging contacts.

44. A system for automatically recommending a media asset based on an interaction, the system comprising

storage circuitry configured to store a media asset database;

and

control circuitry configured to;

process verbal data from an interaction between a user and a person with whom the user is interacting;

cross-reference the processed data with the media asset database to identify a media asset referred to during the interaction;

identify the person with whom the user is interacting based on the processed data;

retrieve, from a database of friends of the user, a recommendation weight corresponding to the identity of the person with whom the user is interacting; and

determine whether to add the identified media asset to a list of media assets associated with the user based on the retrieved recommendation weight corresponding to the identity of the person with whom the user is interacting.

45. The system of claim 44, wherein the control circuitry is further configured to, in response to determining that the identified media asset should be added to the list of media assets, add the identified media asset to the list of media assets associated with the user by adding the identified media asset to a list or queue of media assets to be transmitted to the user, add the identified media asset to a list of media assets recommended to the user, create a bookmark to the identified media asset, create a link to the identified media asset, or schedule a recording of the identified media asset on a device associated with the user.

46. The system of claim 44, wherein the control circuitry is further configured to:

determine, based on an analysis of the verbal data, a level of interest in the identified media asset of at least one of the user and the person with whom the user is interacting.

47. The system of claim 44, wherein the control circuitry is further configured to:

monitor a number of times that the identified media asset was identified within the verbal data;

compare the number of times that the identified media asset was identified to a threshold number, and

in response to the number of times the identified media asset was identified exceeding the threshold number, add the identified media asset to the list of media assets associated with the user.

48. The system of claim 44, wherein the control circuitry is further configured to:

monitor a number of interactions in which the identified media asset was identified;

compare the number of interactions in which the identified media asset was identified to a threshold number; and

in response to the number of interactions in which the identified media asset was identified exceeding the threshold number, add the identified media asset to the list of media assets associated with the user.

49. The system of claim 44, wherein the control circuitry is further configured to:

determine a plurality of candidate media assets based on a profile associated with at least one of the user and the person with whom the user is interacting; and

identify, from the determined list of candidate media assets, a media asset referred to during the interaction by at least one of the user and the person with whom the user is interacting.

50. The system of claim 44, wherein the control circuitry is further configured to:

receive a user input corresponding to the person with whom the user is interacting;

modify, based on the received user input, the recommendation weight corresponding to the identity of the person with whom the user is interacting; and

store the modified recommendation weight in the database of friends of the user.

51. The system of claim 50, wherein the user input indicates favoring the person with whom the user is interacting, and wherein the control circuitry configured to modify the recommendation weight is further configured to increase the recommendation weight.

52. The system of claim 50, wherein the user input indicates ignoring the person with whom the user is interacting, and wherein the control circuitry configured to modify the recommendation weight is further configured to decrease the recommendation weight.

53. The system of claim 44, wherein the database of friends of the user receives information from at least one of the user'"'"'s social network contacts, the user'"'"'s mobile device contacts, the user'"'"'s email contacts, and the user'"'"'s messaging contacts.