Personal Broadcasting Content Recommendation via User-Host Characteristic Matching

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Solution Overview

Problem

Personal broadcasting users spend considerable time searching for content that suits their preferences due to the abundance of channels, and existing methods do not effectively match user characteristics with broadcasting host characteristics.

Innovation Solution

A method that analyzes broadcasting characteristics of personal broadcasting hosts and user characteristics, including user status and preferences, to recommend personalized channels by matching the two, using techniques such as keyword analysis and movement pattern analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If users manually search for broadcasting programs among numerous channels, then they can find content that suits their preferences, but they spend considerable time searching

Engineering Contradiction:

Improvematching accuracy between user preferences and broadcasting contentVSAvoidtime spent searching for broadcasting programs

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system automatically analyzes user characteristics (movement patterns, user status) and broadcasting host characteristics (keyword analysis, content analysis) to perform self-matching, eliminating the need for manual searching while maintaining high matching accuracy

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system continuously collects user data (movement displacement, user status) and broadcasting content data, analyzes characteristics from both sides, and provides real-time personalized recommendations, creating a feedback loop that improves matching over time

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If existing recommendation methods are used, then some recommendations are provided, but they do not effectively match user characteristics with broadcasting host characteristics

Engineering Contradiction:

Improvepersonalization of broadcasting recommendationsVSAvoidmatching accuracy between user and host characteristics

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system segments user characteristics into multiple dimensions (movement patterns, user status, preferences) and broadcasting host characteristics into separate dimensions (keyword analysis, content analysis), enabling comprehensive multi-dimensional matching for highly personalized recommendations

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes the parameters used for matching by incorporating dynamic user status (derived from movement patterns) and broadcasting host characteristics (derived from content analysis), moving beyond static preference matching to dynamic multi-parameter matching

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10462508B2Method of recommending personal broadcasting contents

Publication Date: 2019.10.29 JUNG WOOJU

AI summary

The present invention is related to a method for recommending personal broadcasting contents, comprising analyzing personal broadcasting contents conducted by a personal broadcasting host and analyzing broadcasting characteristics of the personal broadcasting host, determining current user characteristics including at least user status and user preference; and searching for broadcasting characteristics of a personal broadcasting host that matches the current user characteristics and providing at least one recommended personal broadcasting channel.