Inferring User Intent via Hybrid Navigation Path Analysis
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Solution Overview
Problem
The exponential growth of online content lacks a standard organization system, making it difficult for users to find relevant information, as opposed to traditional libraries which use standardized classification systems.
Innovation Solution
A system that infers user intent by analyzing network navigation paths and physical movement paths, using contextual flags to weight recent and repeated behaviors, and groups users based on similar paths to provide targeted content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If no standard organization system is used for web content, then content publishing becomes easier and more accessible, but content location becomes increasingly difficult
Solution Approach 1:
The system uses user navigation paths as feedback to continuously improve content delivery. By tracking and analyzing how users navigate through web content, the system learns from actual user behavior patterns and uses this feedback to infer intent and deliver more relevant content, effectively solving the content location problem without requiring standardized organization
Solution Approach 2:
The system enables self-service by automatically analyzing navigation paths and inferring user intent without requiring manual content classification or user input. The system serves users based on their observed behavior patterns, automatically adapting to individual user needs and preferences
2Measurement precision
If user navigation paths are tracked and analyzed, then content relevance improves, but system complexity increases
Solution Approach 1:
The system introduces an intermediary component that analyzes navigation paths and infers user intent, acting as a mediator between raw navigation data and content delivery decisions. This intermediary layer processes complex path analysis while presenting simplified, relevant content to users, managing system complexity through modular architecture
Solution Approach 2:
The system replaces traditional mechanical content organization methods (manual classification, standardized systems) with automated computational analysis of navigation paths. By using algorithmic intent inference based on observed behavior patterns, the system achieves high content relevance precision without requiring complex manual organization structures
Data Source
AI summary
Paths followed by a plurality of devices are recorded. Devices of the plurality have sent content requests similar to a current content request. Behaviors exhibited by respective ones of the plurality of devices after sending content requests are recorded. The respective ones of the plurality of devices into intent groupings. A path followed by a device is assembled. The assembling the path comprises recording a plurality of physical location readings generated with respect to the device prior. An intent grouping matching the path is identified. The intent grouping is associated with an expected behavior. Content calculated to facilitate the expected behavior is identified.