Concept-Based Information Retrieval for Search Relevance
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Solution Overview
Problem
Traditional information retrieval techniques rely on vocabulary term matching, which often fails to provide relevant documents that do not have matching words or phrases, while also requiring significant human effort to maintain knowledge bases for relevant responses.
Innovation Solution
The technique involves breaking down input phrases into concepts and concept patterns to search for relevant documents, using Vocab Terms, Helper Terms, and Building Blocks, and indexing documents based on these concepts to provide more relevant and concise responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional vocabulary term matching is used to search documents, then the search process is simple and fast, but relevant documents without matching vocabulary words are not retrieved
Solution Approach 1:
The patent introduces concepts as an intermediary layer between vocabulary terms and documents. Instead of directly matching vocabulary terms to documents, the system first maps vocabulary terms to concepts, then uses concepts to retrieve documents. This intermediary concept layer enables retrieval of relevant documents even when exact vocabulary matches are absent, resolving the contradiction between retrieval reliability and mechanism complexity.
Solution Approach 2:
The patent segments the search process into distinct components: vocabulary term processing, concept attribution, and document retrieval. By breaking down the search mechanism into these modular segments, the system can implement sophisticated concept-based matching without overwhelming complexity, as each segment handles a specific aspect of the retrieval process independently.
2Reliability
If knowledge bases are designed to provide appropriate and relevant responses, then response quality improves, but human effort for maintenance and improvement increases significantly
Solution Approach 1:
The patent implements self-service through automated concept attribution and knowledge base unit generation. The system automatically attributes concepts to documents and generates knowledge base units without requiring manual human effort for each addition. This automation maintains high response quality while significantly reducing the time and effort required for knowledge base maintenance and improvement.
Solution Approach 2:
The patent performs preliminary action by pre-attributing concepts to documents and pre-building knowledge base units during system setup or incremental updates. This preliminary processing enables the system to quickly respond to user queries without requiring real-time human intervention, thereby improving response quality while minimizing ongoing maintenance time.
3Measurement precision
If concept-based indexing is implemented, then search relevance improves, but the complexity of document processing increases
Solution Approach 1:
The patent creates a universal concept framework that serves multiple functions: it enables precise document retrieval, supports knowledge base unit generation, and facilitates automated response construction. This multi-functional concept system achieves high measurement precision in information retrieval while managing processing complexity through the reuse of the same concept attribution mechanism across different system functions.
Data Source
AI summary
Various embodiments are described which leverage techniques for breaking down critical ideas from an inputted phrase into concepts in order to provide a response that is more relevant to the inputted phrase. In this regard, concepts and/or concept patterns are utilized with information retrieval searching to provide more relevant and concise documents in response to an inputted phrase. In addition, concepts and/or concept patterns are utilized with respect to assessing information (e.g., documents) available in a knowledge base and building appropriate pre-defined responses to an inputted phrase.