Context-Indexed URL Module for Automatic Resource Matching
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Solution Overview
Problem
Current internet search engines require user input to determine relevant network resources and do not automatically adapt to consumers' current circumstances, such as time, location, or activities, making it difficult to provide context-specific recommendations.
Innovation Solution
A system that uses a context-indexed URL module to determine and store network resources based on temporal, spatial, environmental, or activity circumstances of consumers, allowing for automatic recommendation of relevant resources by matching consumer context with context-indexed URLs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If internet search engines require user input of keywords to determine relevant network resources, then the system can identify specific resources, but it cannot automatically determine relevance based on consumer circumstances
Solution Approach 1:
The system pre-indices network resources with context tokens representing various consumer circumstances (temporal, spatial, environmental, activity) before search queries are submitted. This preliminary organization allows automatic matching of consumer context with relevant resources without requiring manual keyword input, resolving the contradiction between automation and information loss.
Solution Approach 2:
Context tokens serve as intermediaries between consumer circumstances and network resources. The service determines context tokens from consumer context data and uses these tokens to retrieve pre-indexed resources, enabling automatic determination while preserving the relationship between consumer situation and relevant content.
2Adaptability or versatility
If the system stores network resources in association with context tokens, then automatic context-aware recommendations can be provided, but the device complexity increases
Solution Approach 1:
The system segments the context space into distinct context tokens representing different dimensions (temporal, spatial, environmental, activity). Each network resource is indexed with relevant context tokens, allowing the system to handle complexity through structured segmentation rather than monolithic processing.
Solution Approach 2:
The context-indexed storage system serves multiple functions: it stores network resources, organizes them by context, enables automatic retrieval, and supports various query types. This multi-functionality justifies the increased device complexity by consolidating multiple operations into a unified system.
Data Source
AI summary
Techniques to provide context-indexed network resources include determining a network resource that is associated with first data in response to receiving first data that describes a context feature. A context token is determined, which indicates a probability, in the first data, of a topic from a context vocabulary. The context vocabulary includes concepts describing temporal, spatial, environmental or activity circumstances of consumers. Second data is stored, which indicates the network resource in association with the context token. In some embodiments, determining a network resource associated with the first data includes sending a topic based on the feature context token to a network resource search engine; and, the network resource is determined based on data returned from the network resource search engine.