Digital Image Interest Evaluation via Contextual Segmentation
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Solution Overview
Problem
Conventional techniques for evaluating user subject interests from digital image records are simplistic and lack robustness, failing to accurately capture the probabilistic relationships and contextual information essential for understanding user interests.
Innovation Solution
A method and system that analyze a user's digital image records by receiving content requirements, identifying relevant images based on these criteria, and evaluating subject-interest traits using contextual information such as time and location, to associate the user's interests with processor-accessible memory for targeted marketing and promotional approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If conventional techniques decompose image content into data units or labels for objects, then object detection is achieved, but accurate evaluation of user subject interests is lost
Solution Approach 1:
The patent segments the image analysis process into multiple levels: basic object detection (data units), contextual relationship analysis (probabilistic relations), and user interest evaluation (subject interests). This multi-level segmentation allows the system to preserve information at each stage rather than losing it through simple decomposition.
Solution Approach 2:
The patent introduces contextual information as an intermediary element that connects basic object detection with user interest evaluation. This intermediary layer captures probabilistic relationships, temporal patterns, and spatial contexts, preventing information loss between the object labels and user interests.
2Measurement precision
If a comprehensive collection of digital image records is analyzed, then user subject interest evaluation accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary indexing and organization of image records based on contextual metadata (time, location, device information) before the actual interest evaluation. This preliminary action structures the data in advance, enabling faster retrieval and analysis when evaluation is needed.
Solution Approach 2:
The patent analyzes only the subset of image records that are most relevant to specific subject interests, rather than processing the entire collection uniformly. By identifying and focusing on pertinent records based on contextual filters, the system achieves accurate evaluation without the full time cost of comprehensive analysis.
3Measurement precision
If contextual information such as time and location is incorporated into image analysis, then user subject interest evaluation accuracy is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal contextual framework that handles multiple types of information (time, location, device, social context) through a unified processing architecture. This multi-functional approach manages complexity by using consistent methods for diverse contextual data rather than separate specialized systems.
Solution Approach 2:
The patent transforms contextual information into standardized parameters and weights that can be systematically applied across different analysis scenarios. By changing the representation of contextual data into uniform parameters, the system manages complexity through consistent parameter handling rather than diverse processing rules.
Data Source
AI summary
A method of evaluating a user subject interest is based at least upon an analysis of a user's collection of digital image records and is implemented at least in part by a data processing system. The method receives a defined user subject interest, receives a set of content requirements associated with the defined user-subject-interest, and identifies a set of digital image records from the collection of digital image records each having image characteristics in accord with the content requirements. A subject-interest trait associated with the defined user-subject-interest is evaluated based at least upon an analysis of the set of digital image records or characteristics thereof. The subject-interest trait is associated with the defined user-subject-interest in a processor-accessible memory.