Document Tagging with Entity Sentiment Polarity
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Solution Overview
Problem
Current sentiment analysis technologies only provide fragmented knowledge about sentiment polarity, isolating entities and their opinions, and fail to reflect relationships between entities and their sources, limiting comprehensive insights into articles or subjects.
Innovation Solution
A document tagging method and apparatus that acquires focused entities relevant to a basic document, determines their sentiment polarity, and generates tags to facilitate knowledge about opinions on these entities, reflecting associations between entities and their sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sentiment analysis technology is used to analyze sentiment on specific contents, then sentiment polarity can be derived, but only fragmentary knowledge about the polarity is obtained and entities are isolated
Solution Approach 1:
The patent combines multiple isolated sentiment analysis results into a unified document-level view by integrating entity opinions with their source documents. This merging process connects previously isolated entities and their sentiments within the broader document context, preserving relationship information that would otherwise be lost.
Solution Approach 2:
The patent introduces document tags as an intermediary structure that bridges entities and their source documents. These tags serve as mediators that capture and preserve the relationships between entities, their sentiments, and the documents they originate from, preventing information loss about entity relationships.
2Ease of operation
If entities and opinions are isolated for analysis, then sentiment polarity can be determined, but associations between entities and their sources cannot be reflected
Solution Approach 1:
The patent implements a nested structure where entity opinions are nested within document contexts. The tag system creates nested layers of information: entities contain sentiments, which are associated with documents, preserving the hierarchical relationships without complicating the analysis process.
Solution Approach 2:
Document tags act as intermediaries that maintain associations between entities and their source documents while keeping the analysis process simple. The tags carry relationship information without requiring complex processing, enabling both ease of operation and preservation of association information.
3Device complexity
If fragmentary sentiment knowledge is used, then analysis is simpler, but comprehensive insights into articles or subjects cannot be obtained
Solution Approach 1:
The patent creates a universal tag system that serves multiple functions: it preserves entity sentiments, maintains document associations, and enables comprehensive analysis. This multi-functional approach allows the system to remain relatively simple while providing comprehensive insights through the versatile tag structure.
Solution Approach 2:
The patent performs preliminary tagging of entities with their sentiments and document associations before comprehensive analysis. This preliminary action prepares the data in advance, allowing comprehensive insights to be obtained without requiring complex processing during the actual analysis phase.
Data Source
AI summary
A document tagging method and apparatus. According to the method, a focused entity relevant to a basic document and a sentiment polarity of comments on the focused entity are acquired, and then a tag is generated on the basic document from the focused entity and the corresponding sentiment polarity. The present invention can tag the basic document with an opinion on the relevant focused entity and thus facilitate knowledge of the opinion on a relevant entity.