User-Customized Content Delivery via Ontology-Based Matching

Solution Overview

Problem

Current information retrieval systems are inefficient as users often need to perform multiple searches to find desired content, and they do not actively cater to user requests, leading to time-consuming and costly content retrieval.

Innovation Solution

A method and system for providing user-customized content by constructing and utilizing metadata-based databases to match user content orders with provider content, using ontologies to organize and filter information, allowing users to receive specific content through designated terminals at desired times and volumes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If users perform multiple retrieval operations to acquire desired contents, then the precision of information retrieval is improved, but the time and cost for content retrieval increase

Engineering Contradiction:

Improveprecision of information retrievalVSAvoidtime for content retrieval

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary actions by proactively retrieving and preparing contents based on user profiles and predicted interests before users actually search for them. The server anticipates user needs and makes relevant contents ready in advance, eliminating the need for multiple iterative searches by users.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms where user retrieval behavior, preferences, and interactions are continuously monitored and fed back into the system. This feedback loop enables the system to refine its understanding of user needs and improve the accuracy of proactive content delivery over time, reducing the number of searches users need to perform.

Inventive Principle:

Principle #23Feedback

2Extent of automation

If information retrieval systems filter and extract information based on user search words, then the system operation is automated, but the system does not actively deal with users' requests

Engineering Contradiction:

Improveautomation of information retrievalVSAvoidability to actively deal with users' requests

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The system performs preliminary actions by proactively retrieving and preparing contents based on user profiles and predicted interests before users actually search for them. The server anticipates user needs and makes relevant contents ready in advance, eliminating the need for multiple iterative searches by users.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system inverts the traditional retrieval model where users initiate searches. Instead, the system initiates content delivery by predicting user needs and proactively providing relevant contents. This inversion transforms the passive search-based model into an active recommendation-based model that truly adapts to user requests.

Inventive Principle:

Principle #13The other way round (Inversion)

3Measurement precision

If users spend large amount of time for contents retrieval, then the precision of information retrieval is improved, but the productivity of content acquisition deteriorates

Engineering Contradiction:

Improveprecision of information retrievalVSAvoidproductivity of content acquisition

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system performs preliminary actions by proactively retrieving and preparing contents based on user profiles and predicted interests before users actually search for them. The server anticipates user needs and makes relevant contents ready in advance, eliminating the need for multiple iterative searches by users.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by automatically understanding user needs and delivering relevant contents without requiring users to manually search or refine queries. The system serves itself by using its own data about user behavior and preferences to automatically fulfill content acquisition needs, dramatically improving productivity.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS9514425B2Method and system for providing user-customized contents

Publication Date: 2016.12.06 NEOPAD

AI summary

A method for providing user-customized contents, includes: receiving contents order information from a user and constructing a contents order information DB; opening the contents order information DB; receiving contents corresponding to the contents order information from a contents provider; and providing the received contents in a user-customized form.