Narrative Generation Triggering via Story Angle Evaluation
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Solution Overview
Problem
Existing systems for automatically generating narrative stories from data lack effective criteria to determine when and how to generate stories, leading to inefficiencies and irrelevant content.
Innovation Solution
A method and apparatus that evaluate data against a set of story angles and applicability conditions to determine whether a narrative story should be generated, using a processor to access an angle set data structure and compute an evaluation indicator based on processed data, thereby deciding on story generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If narrative stories are automatically generated from all available data, then the quantity of content produced increases, but the relevance and quality of the content deteriorates
Solution Approach 1:
The system performs preliminary evaluation of data against multiple story angles and applicability conditions before generating narratives. This pre-screening process ensures that only data meeting specific relevance criteria triggers story generation, maintaining content quality while enabling automated production of relevant stories.
Solution Approach 2:
The system uses evaluation indicators derived from comparing data against story angles and applicability conditions to determine whether to generate stories. This feedback mechanism ensures that story generation is triggered only when the data satisfies relevant criteria, thereby maintaining content relevance while enabling automated production.
2Reliability
If multiple story angles and applicability conditions are evaluated against data, then the relevance of generated stories improves, but the system complexity increases
Solution Approach 1:
The evaluation system is segmented into distinct story angles, each with its own set of applicability conditions. This modular structure allows the system to evaluate data against multiple specific angles independently, improving story relevance while managing complexity through organized, discrete evaluation units.
Solution Approach 2:
The system dynamically selects and applies relevant story angles and their corresponding applicability conditions based on the characteristics of the input data. This dynamic approach allows the system to adapt its evaluation criteria to the specific data being processed, improving relevance without requiring all possible angles to be active simultaneously, thus managing complexity.
3Productivity
If automated story generation is triggered based on data evaluation, then the efficiency of content creation improves, but the risk of generating irrelevant or inappropriate content increases
Solution Approach 1:
The system performs preliminary evaluation of data against story angles and applicability conditions before triggering story generation. This pre-screening process ensures that only data meeting relevant criteria initiates content creation, improving efficiency while preventing generation of irrelevant or inappropriate content.
Solution Approach 2:
The system uses evaluation indicators derived from comparing data against story angles and applicability conditions to control story generation triggering. This feedback mechanism ensures automated content creation occurs only when appropriate, improving efficiency while filtering out irrelevant or inappropriate content generation.
Data Source
AI summary
Artificial intelligence methods and systems for triggering the generation of narratives are disclosed. Specific embodiments relate to real-time evaluation and automated generation of narrative stories based on received data. For example, data can be tested against data representative of a plurality of story angles to determine whether a narrative story incorporating one or more such story angles is to be automatically generated.