Content Recommendation Combining Process for Personalization

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Solution Overview

Problem

Existing content recommendation systems face challenges in providing timely and personalized content recommendations due to time constraints and the need for system updates, especially in systems with millions of subscribers.

Innovation Solution

A computer-implemented method and system that perform a combining process using multiple content recommendation procedures to generate personalized content recommendations for users. This involves opening a content recommendation session, receiving content recommendation requests, processing them using selected procedures, and providing the results to further procedures for filtering, ranking, and sorting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If multiple content recommendation procedures are combined to improve personalization quality, then recommendation accuracy improves, but system complexity increases

Engineering Contradiction:

Improverecommendation accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the recommendation system into multiple independent procedures (e.g., collaborative filtering, content-based filtering, hybrid approaches) that can be selectively combined. Each procedure handles specific aspects of recommendation generation, allowing the system to achieve high accuracy through modular composition rather than monolithic complexity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent creates a universal framework that can accommodate multiple different recommendation procedures within a single system architecture. This multi-functional approach allows the same system to perform various recommendation tasks using different procedures, reducing overall system complexity while maintaining high recommendation accuracy.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Measurement precision

If comprehensive content analysis is performed to improve recommendation quality, then personalization improves, but processing time increases

Engineering Contradiction:

Improvepersonalization qualityVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent performs preliminary actions by pre-processing and indexing content metadata, user profiles, and recommendation candidates before actual recommendation requests arrive. This advance preparation enables faster processing during real-time recommendation generation while maintaining comprehensive analysis quality.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent applies partial action by selectively analyzing only the most relevant features and procedures needed for each specific recommendation request, rather than performing exhaustive analysis on all available data. This reduces processing time while maintaining sufficient personalization quality.

Inventive Principle:

Principle #16Partial or excessive action

3Ease of operation

If real-time recommendations are provided to meet user expectations, then user experience improves, but system performance under load deteriorates

Engineering Contradiction:

Improveuser experienceVSAvoidsystem performance

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The patent implements periodic action through asynchronous recommendation generation and batch processing techniques. Instead of requiring all recommendations to be generated synchronously in real-time, the system uses periodic updates and background processing to maintain user experience while managing system performance under heavy load.

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The patent introduces intermediary components such as recommendation caches, pre-computed candidate lists, and buffering mechanisms that mediate between user requests and the complex recommendation procedures. These intermediaries reduce the immediate processing burden on the system while still providing timely recommendations to users.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12335548B2System and methods for performing content recommendation procedures

Publication Date: 2025.06.17 THINKANALYTICS

AI summary

A computer-implemented method for providing content recommendations for a user of a content distribution system, the method comprising:opening a content recommendation session for a selected user, wherein a plurality of data processing procedures, or operations, are available for use during the content recommendation session, the plurality of data processing procedures comprising at least one type of content recommendation procedure for generating one or more content recommendation candidates based on user data and/or content metadata and/or other content information; wherein the method further comprises performing a combining process using one or more of the plurality of procedures to generate one or more content recommendation candidates, wherein the combining process comprises at least: receiving at least one content recommendation request for the selected user; processing said at least one request using at least a first procedure selected from the plurality of procedures to generate at least one or more content recommendation candidates; providing at least some of the one or more content recommendation candidates to at least a second procedure selected from the plurality of procedures to generate at least one or more further content candidates.