Opinion Data Management via Structured Tuple Extraction
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Solution Overview
Problem
Current methods for managing opinion data are inefficient and difficult to use for decision support due to the unstructured nature of text sources containing user opinions, sentiments, and other information, making it challenging to extract and utilize this data effectively.
Innovation Solution
A method and apparatus for managing opinion data that involves acquiring opinioned sentences from text sources, extracting opinion tuples with opinion words and targets, determining sentiment values, and storing this information in association with source data, allowing for classification and retrieval of relevant opinions for decision-making purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If opinion data are stored in unstructured text sources, then the data can be acquired from various sources, but it is difficult to make all-round statistics and use them to support decision making
Solution Approach 1:
The patent segments unstructured text data into structured opinion tuples containing opinion holder, opinion target, opinion words, and sentiment values. This segmentation transforms raw text into organized units that can be efficiently aggregated and analyzed, resolving the contradiction between maintaining data source versatility and improving analysis efficiency.
Solution Approach 2:
The patent changes the parameter representation of opinion data by extracting and storing sentiment values as quantifiable parameters. This transformation enables statistical aggregation and computational analysis of opinion data, converting unstructured text into a format suitable for decision support while preserving the original data sources.
2Loss of information
If all opinion data are extracted and stored in detail, then comprehensive opinion information is available, but the storage and processing complexity increases
Solution Approach 1:
The patent extracts only the essential components from complete text data - specifically opinion holder, opinion target, opinion words, and sentiment values. This selective extraction maintains the completeness of opinion information while reducing storage requirements and simplifying data management by storing only the structured tuple elements rather than full text.
3Measurement precision
If opinion data are processed manually, then accurate extraction can be achieved, but the processing time and resource consumption increase
Solution Approach 1:
The patent replaces manual mechanical processing with automated computational methods including syntactic parsing and sentiment analysis algorithms. This substitution maintains extraction accuracy through systematic rule-based approaches while dramatically increasing processing speed and reducing resource consumption compared to manual analysis.
Data Source
AI summary
Embodiments of the present invention provide a method and apparatus for managing opinion data. In an embodiment, there is provided a method for managing opinion data. The method comprises: acquiring an opinioned sentence from one or more text sources; extracting an opinion tuple based on the opinioned sentence, the opinion tuple at least containing an opinion word and an opinion target. The method further comprises: storing in association the opinioned sentence, opinion tuple and source information corresponding to the opinioned sentence, wherein the source information is associated with the text source from which the opinioned sentence is acquired. The opinioned sentence, the opinion tuple and the source information acquired from the text sources are stored in association by using for example an XML storage format so that the stored opinion data are associated to a certain degree, and the stored opinion data are easily extended and modified.