Categorical Touch Text Search for Smartwatch Portability
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Solution Overview
Problem
Existing text search systems face challenges in portability and accessibility, particularly on devices like smartwatches, due to the reliance on physical keyboards and the need for precise keyword input, which limits users' ability to efficiently navigate through large volumes of textual information, especially when recalling concepts rather than specific terms.
Innovation Solution
A computer-implemented method utilizing categorical touch inputs to search text, which organizes written works into slices, filters them based on user inputs such as clusters or manual tags, and displays the results in a color-coded grid, allowing for phonetic-based sorting and categorization, enabling keyboard-less searching on touch-enabled devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical keyboard input is used for text search, then search precision is improved, but device portability and accessibility are worsened
Solution Approach 1:
The patent replaces the mechanical keyboard input system with a touchscreen interface that accepts various input methods including voice commands, gestures, and soft keyboards. This substitution eliminates the dependency on physical keyboards while maintaining search functionality across diverse devices like smartphones, tablets, and smartwatches, thereby resolving the contradiction between search precision and device portability.
Solution Approach 2:
The search system is designed to support multiple input methods (touchscreen, voice, gestures, soft keyboard) and adapt to different device types. This multi-functional approach allows the same search engine to operate effectively across smartphones, tablets, smartwatches, and other devices without requiring physical keyboards, thus achieving both precision and versatility.
2Measurement precision
If precise keyword input is required, then search accuracy is improved, but user accessibility is worsened
Solution Approach 1:
The patent introduces intermediate processing layers including voice-to-text conversion, gesture recognition, and intelligent query refinement that bridge the gap between casual user input and precise search requirements. These intermediaries automatically enhance user input without requiring users to manually formulate precise keywords, thereby maintaining search accuracy while improving accessibility.
Solution Approach 2:
The search system automatically performs query refinement, suggestion generation, and result ranking without requiring users to manually optimize their search terms. The system self-adjusts to interpret user intent and deliver accurate results even with imprecise input, eliminating the burden of precise keyword formulation while maintaining search effectiveness.
3Measurement precision
If manual text filtering is used, then search precision is improved, but operation complexity is worsened
Solution Approach 1:
The patent implements pre-filtering mechanisms that automatically organize and categorize search results before presentation to the user. Results are pre-sorted by relevance, with filtering criteria applied in advance based on user profile, search history, and contextual information. This preliminary processing reduces the complexity of manual filtering while maintaining high precision.
Solution Approach 2:
The filtering system dynamically adapts to user behavior and preferences, automatically adjusting filter criteria and result presentation based on interaction patterns. The system learns from user feedback and refines its filtering algorithms in real-time, reducing the need for manual intervention while maintaining precision. Filtering complexity is managed dynamically rather than through static, rigid processes.
Data Source
AI summary
A computer implemented method for searching text utilizing categorical touch inputs, the method comprising: obtaining a written work; organizing the written work into one or more stories, the one or more stories comprised of one or more slices; filtering the one or more slices via a user input, the user input comprising at least one of a plurality of clusters and a manual tag; generating a text of the written work, the text of the written work derived from the one or more slices; displaying, via a display, the text of the written work; color-coding the text of the written work creating color-coded text; displaying, via the display, the color-coded text in a table; generating a grid comprised of one or more colors, the grid having an equal number of columns and rows as the table, and the one or more colors corresponding to the color-coded text in the table.