Dynamic Information Filtering for Mobile Context Adaptation
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Solution Overview
Problem
Current search technologies fail to effectively understand user intent and adapt to changing user contexts, particularly for mobile users, leading to irrelevant search results.
Innovation Solution
A computer-implemented method for information filtering that stores user goals and continuously filters search results based on changing user context, including location, preferences, and device type, to provide relevant information on the appropriate device modality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional keyword-based search is used, then search speed is fast, but relevance to user intent is poor
Solution Approach 1:
The patent implements dynamic filtering that continuously adapts to changing user context (location, device, time, preferences) rather than using static keyword matching. The system dynamically adjusts search results based on real-time context changes, making the search process adaptive and responsive to user needs.
Solution Approach 2:
The system incorporates user context information as feedback to continuously refine and filter search results. By monitoring user location, device type, time, and preferences, the system uses this feedback loop to improve relevance without requiring complex manual configuration.
2Measurement precision
If search results are filtered based on multiple context factors, then relevance improves, but processing time increases
Solution Approach 1:
The system pre-processes and stores user context information (preferences, historical choices, device characteristics) before search is needed. This preliminary preparation allows the filtering process to occur quickly during actual search operations, as the context data is already structured and ready for application.
Solution Approach 2:
The patent changes the parameters used in filtering from static keywords to dynamic context parameters (location, device, time, preferences). By transforming the search methodology to use these contextual parameters, the system achieves better relevance while maintaining efficient processing through optimized parameter comparison.
3Productivity
If search results are continuously updated based on context changes, then timeliness improves, but system complexity increases
Solution Approach 1:
The system implements continuous filtering that operates ongoing as user context changes, rather than performing discrete batch updates. This continuous action ensures search results remain timely and relevant without requiring complex periodic re-processing, as the filtering mechanism continuously adapts to context changes.
Solution Approach 2:
The patent creates a universal filtering framework that handles multiple context factors (location, device, time, preferences) through a single integrated system. This multi-functional approach avoids the need for separate complex systems for each context factor, achieving timeliness through a unified continuous filtering mechanism.
Data Source
AI summary
In one embodiment the present invention includes a computer-implemented method of information filtering. The method includes storing a user goal. The method further includes generating search results corresponding to the user goal. The method further includes continuously filtering the search results, based on a user context that changes, to obtain a filter result related to the user goal. The method further includes outputting the filter result in accordance with a current user device.