Text Transformation System for Dynamic Writing Suggestions
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Solution Overview
Problem
Writers face challenges such as writer's block, lack of inspiration, and difficulty in structuring content due to time constraints and the need for novel topics, exacerbated by the pressure to produce high-quality work under tight deadlines, especially in the fast-paced environment of blogging and social media, where they often lack access to relevant information and struggle with basic writing principles like the 'Five Ws' and 'One H'.
Innovation Solution
A computer-implemented method and system that receives unstructured text, disassembles it into individual words, tags them by speech type, chunks them into phrases to form a tree-like structure, generates suggestions, and ensures proper tense and singular/plural form, providing real-time dynamic writing prompts and engagement questions to aid in content creation, learning the author's writing style to present relevant and thought-provoking suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If authors perform research and gather information manually before writing, then they can address the Five Ws and One H effectively, but the process becomes disruptive, time-consuming, and inefficient
Solution Approach 1:
The system performs preliminary actions by automatically gathering, organizing, and presenting relevant information (Five Ws and One H) before the author begins writing. The suggestion engine pre-processes research data and structures it in advance, eliminating the need for manual information gathering during the writing process.
Solution Approach 2:
The suggestion engine acts as an intermediary between external information sources and the author. It automatically retrieves, processes, and presents relevant information in a structured format, mediating the complex task of research and information organization so the author can focus on writing.
2Loss of information
If authors abandon writing to perform research and gather information, then they can find relevant details, but the writing process is disrupted and productivity decreases
Solution Approach 1:
The system provides continuous feedback during the writing process by monitoring the author's progress and dynamically generating suggestions based on the Five Ws and One H framework. This real-time feedback ensures relevant information is discovered without interrupting the writing flow, maintaining both information completeness and productivity.
Solution Approach 2:
The system enables continuity of useful action by allowing the author to write continuously while the suggestion engine simultaneously provides research information and structural guidance. The writing process and information gathering occur in parallel rather than sequentially, maintaining productive momentum.
3Ease of operation
If authors lack access to relevant information and writing principles, then they struggle to answer Five Ws and One H, but providing all information upfront increases complexity and time requirements
Solution Approach 1:
The system segments the complex task of writing guidance into discrete, manageable components corresponding to the Five Ws and One H. Each principle is presented as a separate suggestion category, allowing authors to access specific guidance without being overwhelmed by the entire system's complexity.
Solution Approach 2:
The system applies local quality by providing context-specific suggestions tailored to the author's current writing needs and progress. Rather than presenting all information uniformly, the suggestion engine adapts its output to the specific section being written, delivering appropriate guidance at the right moment without increasing overall system complexity.
Data Source
AI summary
A system for transforming unstructured text into at least one suggestion for content creation, the system having: a tagging module having instructions in memory, said instructions executable by a processor to receive unstructured text from external sources having at least one sentence; disassemble said at least one sentence into individual words; and tag said individual words by determining a speech type for each of said individual works; a chunking module having instructions in memory, said instructions executable by a processor to said individual words together into phrases to form a tree-like structure of the text, when said individual words are tagged correctly; and a suggestion module having instructions in memory, said instructions executable by a processor to generate said at least one suggestion based on said chunking.