Semantic Relationship Identification for Search Accuracy
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Solution Overview
Problem
Conventional online search engines are limited in recognizing semantic relationships between query keywords and document content, leading to irrelevant search results, as they rely on exact keyword matches and restrict users to predefined keywords, preventing precise expression of information needs.
Innovation Solution
A computer-implemented method that develops semantic relationships between document elements and query terms, generating semantic representations for indexing and propositions to compare against, enabling the retrieval of highly relevant search results by identifying 'about' relationships and associating reporting acts with relevant content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional online search engines use exact keyword matching, then the search process is simple and fast, but the search results are not relevant or meaningful
Solution Approach 1:
The patent introduces semantic relationships as an intermediary layer between keywords and document content. Instead of directly matching keywords to documents, the system first establishes semantic relationships (such as hypernym, synonym, part-whole relationships) between search terms and document elements, then uses these relationships to retrieve relevant documents. This mediator layer enables the system to understand the meaning behind words rather than just matching exact strings, thereby improving search accuracy while maintaining a manageable system architecture through structured relationship definitions.
2Adaptability or versatility
If conventional search engines rely on exact keyword matches, then the matching process is straightforward, but users cannot precisely express information needs with unknown keywords
Solution Approach 1:
The patent changes the parameter of keyword matching from exact string equality to semantic equivalence. By defining and utilizing semantic relationships (hypernym, synonym, part-whole, coordinate relationships), the system transforms the matching criterion from rigid exact matches to flexible semantic matches. This allows users to express information needs more naturally and accurately, even when the precise keywords are unknown, as the system can infer meaning through established semantic relationships between terms.
3Reliability
If conventional search engines do not recognize semantic relationships, then the processing is simple, but the search results lack relevance to the query meaning
Solution Approach 1:
The patent segments the search process into distinct components: (1) establishing semantic relationships between search terms and document elements, (2) retrieving documents containing these elements, and (3) ranking results based on relationship strength. By dividing the complex task of semantic search into manageable segments with clear boundaries, the system achieves reliable search results while controlling overall complexity. Each segment can be independently optimized and maintained, making the sophisticated semantic processing more tractable.
Data Source
AI summary
Methods and computer-readable media for associating words or groups of words distilled from content, such as reported speech or an attitude report, of a document to form semantic relationships collectively used to generate a semantic representation of the content are provided. Semantic representations may include elements identified or parsed from a text portion of the content, the elements of which may be associated with other elements that share a semantic relationship, such as an agent, location, or topic relationship. Relationships may also be developed by associating one element that is in relation to, or is about, another element, thereby allowing for rapid and effective comparison of associations found in a semantic representation with associations derived from queries. The semantic relationships may be determined based on semantic information, such as potential meanings and grammatical functions of each element within the text portion of the content.