Logogram Input via Sub-Logogram Segmentation
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Solution Overview
Problem
Entering logograms into input devices is complex due to their numerous strokes and associations with other logograms and phrases, making it difficult for users unfamiliar with all strokes to accurately input them.
Innovation Solution
An apparatus and method that includes an input device, processor, and memory to identify logogram inputs as context logograms or sub-logograms, displaying either a selected logogram or a hint list of candidate logograms to facilitate rapid and accurate entry by users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users enter logograms using traditional stroke-by-stroke methods, then complete logogram input is achieved, but input complexity and time consumption increase significantly
Solution Approach 1:
The patent segments a complete logogram into multiple sub-logograms (components or radicals). Users can input logograms by entering these smaller sub-logogram units rather than tracing all strokes, significantly reducing input complexity while maintaining accuracy. The system divides the complex logogram input task into manageable sub-tasks that are easier for users to perform.
Solution Approach 2:
The system pre-processes and stores logogram data including sub-logogram compositions, stroke sequences, and contextual associations in advance. When a user inputs a sub-logogram, the system has already prepared candidate logogram lists and contextual information, enabling rapid display of relevant options without requiring the user to manually navigate through all possible logograms.
2Measurement precision
If users input complete logograms with all strokes, then accurate logogram entry is achieved, but time consumption increases
Solution Approach 1:
The system allows users to input only partial information (a subset of complete strokes or just key sub-logograms) rather than requiring all strokes to be entered. The system then uses pattern matching and contextual analysis to identify the intended logogram from candidate lists, achieving accurate input with reduced time investment.
Solution Approach 2:
The system provides real-time feedback by displaying candidate logogram lists as users input sub-logograms or stroke sequences. This feedback mechanism allows users to confirm or correct their input by selecting from displayed options, ensuring accuracy while reducing the time needed to complete logogram entry compared to traditional methods.
3Adaptability or versatility
If the system displays all candidate logograms, then complete logogram options are provided, but information overload occurs
Solution Approach 1:
The system applies different levels of detail and filtering to different portions of the candidate logogram list based on contextual relevance. Highly probable candidates are displayed with more prominence or additional contextual information, while less likely candidates are filtered or displayed with less detail, optimizing the information presentation to match user needs and reduce cognitive load.
Solution Approach 2:
The system pre-filters and ranks candidate logograms based on contextual analysis, frequency data, and pattern matching before displaying them to the user. This preliminary processing ensures that the most relevant candidates appear first in the display, allowing users to make selections quickly without being overwhelmed by the complete set of possible logograms.
4Measurement precision
If the system requires users to know all strokes and associations, then complete logogram recognition is achieved, but ease of operation decreases
Solution Approach 1:
The system breaks down complex logogram recognition into simpler sub-logogram recognition tasks. Users only need to recognize and input familiar sub-logogram components or radicals rather than requiring knowledge of all possible logogram strokes and variations. The system handles the complex pattern matching and recognition of complete logograms from these simpler inputs.
Solution Approach 2:
The system introduces an intermediary processing layer that translates simple user inputs (sub-logograms or partial stroke sequences) into complete logogram identifications. This intermediary system performs the complex pattern matching, contextual analysis, and candidate ranking, shielding users from the complexity of logogram structure and associations while maintaining accurate recognition.
Data Source
AI summary
For displaying a logogram indication, a processor identifies a logogram input received from an input device. The logogram input is selected from the group consisting of a context logogram and a sub-logogram. The processor further displays a logogram indication selected from the group consisting of a selected logogram and a logogram hint list of candidate logograms in response to identifying the logogram input.