Personalized Media Recommendation Engine with Automatic Calendar Integration

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Solution Overview

Problem

Traditional media program guides are not tailored to individual user interests and fail to remind users of upcoming programs they may want to watch.

Innovation Solution

A system and method that uses a computer system with processors and memory to receive user requests for media program recommendations, generate search queries based on user preferences and web activity data, and automatically send calendar events or reminders for recommended programs to user-designated calendars without user interaction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional media program guides are used, then users can view program lists for particular channels, but the guides are not tailored for each individual's interests and do not remind users of when programs of interest will be played

Engineering Contradiction:

Improvepersonalization of program recommendationsVSAvoidsystem complexity for generating recommendations

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by collecting user profile information, viewing history, and preferences in advance. This pre-collected data is then used to automatically generate personalized program recommendations without requiring complex real-time analysis, thus resolving the contradiction between personalization and system complexity

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by automatically generating and sending program recommendations to users based on their stored profiles and preferences. The automated recommendation engine eliminates the need for manual curation or complex user interactions, achieving personalization while maintaining simple system operation

Inventive Principle:

Principle #25Self-service

2Reliability

If automated recommendation system is implemented, then users receive personalized program recommendations with reminders, but the system requires complex data processing and user profile management

Engineering Contradiction:

Improveaccuracy of program recommendationsVSAvoidcomplexity of recommendation system

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The recommendation system is segmented into distinct functional modules: user profile management, viewing history analysis, recommendation generation, and notification delivery. This modular architecture improves recommendation accuracy through specialized processing in each module while reducing overall system complexity through clear separation of concerns

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements feedback mechanisms where user responses to recommendations (viewing behavior, ratings, preferences) are continuously collected and used to refine future recommendations. This feedback loop enhances recommendation reliability while the automated nature of the feedback processing keeps system complexity manageable

Inventive Principle:

Principle #23Feedback

3Ease of operation

If manual user interaction is required for calendar setup, then users have control over their calendars, but the process becomes time-consuming and inconvenient

Engineering Contradiction:

Improveease of calendar integrationVSAvoidtime for user to set up and manage calendars

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-configuring calendar integration options and automatically populating calendar events with program recommendation details. Users only need to provide basic calendar access permissions in advance, eliminating the need for time-consuming manual setup while maintaining user control over their calendar data

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by automatically managing calendar event creation, updating, and notification delivery without requiring ongoing user intervention. Once initial permissions are granted, the system handles all calendar operations autonomously, significantly reducing the time users spend on calendar management while maintaining ease of operation

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS10402437B2System and method for recommending media programs and notifying a user before programs start

Publication Date: 2019.09.03 GOOGLE LLC

AI summary

The various implementations described herein include methods and systems for personalized media program recommendations. In one aspect, a method is performed at a server system having processors and memory. The server system: (1) receives, from a client device, a user request for a media program event recommendation; (2) prior to receiving the user request, collects and stores user search history data associated with media program events; (3) creates a search query in accordance with the user request based on the user search history and a portion of the user request; (4) executes the search query against databases to generate media program event recommendations; (5) ranks the generated media program event recommendations; and (6) sends automatically to a calendar associated with the user, a calendar event corresponding to a respective media program event recommendation.