Annotation Summarization for Text Analytics Redundancy
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Solution Overview
Problem
Text analytics frameworks like UIMA generate excessive and redundant annotations when analyzing unstructured data, such as medical evaluation reports, leading to cumbersome analysis results due to the broad extraction of terms like 'pain' and related injuries.
Innovation Solution
A method and system that receive annotations, sort and normalize them, determine topics, group and summarize annotations based on these topics, and replace redundant annotations with summarized ones on the analyzed data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If text analytics frameworks extract all possible terms and annotations from unstructured data, then the completeness of information extraction is improved, but the redundancy and cumbersomeness of analysis results increases
Solution Approach 1:
The patent merges multiple related annotations into a single consolidated annotation. For example, multiple annotations about pain locations, injury types, and symptoms are combined into one comprehensive annotation that preserves all information without redundancy. This directly addresses the contradiction by maintaining information completeness while eliminating result redundancy.
Solution Approach 2:
The patent creates a multi-functional annotation system where a single annotation can serve multiple purposes - representing different injury types, locations, and symptoms simultaneously. This universal annotation structure allows the system to extract all necessary information while presenting it in a non-redundant format.
2Measurement precision
If text analytics frameworks annotate all instances of terms like 'pain' and related injuries, then the thoroughness of analysis is improved, but the ease of interpreting results deteriorates
Solution Approach 1:
The patent combines multiple detailed annotations into consolidated annotations that maintain analytical thoroughness while improving interpretability. By merging related findings into unified annotations with structured attributes, the system preserves measurement precision while making results easier to interpret.
Solution Approach 2:
The patent segments the annotation information into organized categories and hierarchical structures. Instead of presenting a flat list of all annotations, the system segments them by type, location, and severity, making the thorough analysis results more interpretable while maintaining completeness.
3Measurement precision
If text analytics frameworks generate detailed annotations for every extracted term, then the accuracy of data extraction is improved, but the productivity of analysis workflow deteriorates
Solution Approach 1:
The patent merges multiple extraction operations into a single consolidated annotation process. By combining multiple detailed extractions into unified annotations, the system maintains extraction accuracy while reducing the total number of processing steps, thereby improving workflow productivity.
Solution Approach 2:
The patent performs preliminary grouping and consolidation of annotations during the extraction phase itself. By organizing and merging annotations before final output generation, the system maintains accuracy while streamlining the overall workflow, improving productivity without sacrificing extraction precision.
Data Source
AI summary
A method for providing annotation summaries for annotations is provided. The method may include receiving annotations associated with analyzed unstructured data. The method may further include sorting the received annotations. Additionally, the method may include receiving focal points on the analyzed unstructured data. The method may also include extracting the sorted annotations associated with the focal points. The method may further include normalizing terms and phrases associated with the extracted annotations. The method may also include determining topics based on the normalized terms and phrases associated with the extracted annotations. The method may further include grouping the extracted annotations based on the determined topics. The method may also include summarizing the grouped annotations to generate a summarized annotation. The method may further include replacing the extracted annotations with the summarized annotation. The method may also include presenting the summarized annotation in place of the extracted annotations.