Concept Visualization in Information Retrieval Systems
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Solution Overview
Problem
Information retrieval systems face challenges in handling ambiguous queries, as existing techniques struggle to optimize for multiple query interpretations, leading to suboptimal results and user experience.
Innovation Solution
A system that visualizes concepts within an attribute space by analyzing document sets, determining similarity, and generating a graphical model to reflect similarity, using techniques like relative entropy to measure distinctiveness and salience, thereby improving query processing and user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional information retrieval techniques are used to handle ambiguous queries, then the system can process queries using standard methods, but the retrieval accuracy and user experience deteriorate due to inability to optimize for multiple query interpretations
Solution Approach 1:
The patent transforms the ambiguous query processing problem from a linear search approach into a multi-dimensional conceptual space. By mapping queries and documents into an attribute space with multiple dimensions (concepts, their meanings, and relationships), the system can simultaneously evaluate multiple query interpretations across different dimensional axes, resolving ambiguity through spatial relationships rather than sequential processing
Solution Approach 2:
The patent introduces a conceptual space as an intermediary layer between the query and the document collection. This conceptual space acts as a mediator that transforms ambiguous queries into structured concept representations, enabling the system to navigate and retrieve relevant documents through concept-based relationships rather than direct text matching, thereby improving retrieval accuracy for ambiguous queries
2Ease of operation
If the system provides detailed visualization of concepts and their relationships, then user understanding and query refinement improve, but the system complexity and computational requirements increase
Solution Approach 1:
The patent segments the complex information retrieval system into distinct functional components: query processing module, conceptual space construction module, similarity computation module, and visualization module. Each module handles a specific aspect of the retrieval process, allowing the system to manage complexity through modular design while providing comprehensive concept visualization to users through the coordinated operation of these segmented components
Data Source
AI summary
A system for visualizing concepts within a collection of information analyzes a set of materials from at least one collection of information and defines an attribute space associated with the set of materials. The system then determines automatically similarity of members of the attribute space. The system then generates a graphical model of the members of the attribute space, where the generating includes generating a display of the members of the attribute space, each of the members having a respective display distance from other respective members of the attribute space reflective of the determined similarity.