Natural-Language Semantic Search for Mobile Data Visualization
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Solution Overview
Problem
Large computer systems like enterprise and cloud systems lack user-friendly interfaces for data access, requiring sophisticated query structures and terminology, making it difficult for users to locate information without proper training, and mobile devices complicate data presentation and access.
Innovation Solution
A data analytic system that allows users to input queries in natural language, identifies semantic meaning, and generates visual representations of data without syntax, enabling efficient retrieval and presentation on mobile devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional database query interfaces are used, then data access capability is maintained, but user accessibility deteriorates due to requirement of sophisticated query structures and terminology
Solution Approach 1:
The patent introduces a natural language processing intermediary layer between the user and the database query system. This intermediary translates user-friendly natural language inputs into structured query language, eliminating the need for users to learn complex query syntax while maintaining full database access capability. The system acts as a mediator that converts between different language formats.
Solution Approach 2:
The patent replaces the mechanical system of structured query language syntax with a natural language processing system. Instead of requiring users to follow rigid query structure rules, the system uses semantic analysis and machine learning to interpret natural language intent and generate appropriate queries, substituting mechanical syntax rules with intelligent language understanding.
2Measurement precision
If complex query structures are required for data access, then data retrieval precision is maintained, but processing time increases due to endless processing to locate data
Solution Approach 1:
The patent implements preliminary action by pre-processing and indexing natural language queries during system initialization or data loading phases. The system pre-computes semantic relationships, entity mappings, and query patterns, storing them in optimized data structures. When users submit queries, the system retrieves pre-computed results rather than performing full semantic analysis in real-time, significantly reducing processing time while maintaining precision.
3Ease of operation
If traditional search interfaces are used, then system capability is maintained, but user understanding deteriorates due to responses not being presented in understandable formats
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the output format parameters based on the user's query intent and the type of data retrieved. The system transforms raw database results into various presentation formats such as natural language summaries, visualizations, charts, or structured tables, changing the parameters of information delivery to match user comprehension needs rather than database storage formats.
4Adaptability or versatility
If mobile devices are used for data access, then user mobility is improved, but data presentation complexity increases due to limited display capabilities
Solution Approach 1:
The patent applies segmentation by dividing complex data presentations into smaller, manageable segments suitable for mobile device displays. The system breaks down large datasets into paginated results, hierarchical information structures, or modular visualizations that can be progressively revealed. This segmentation allows mobile users to access comprehensive data without being overwhelmed by the complexity of displaying all information simultaneously on limited screens.
Data Source
AI summary
Techniques are disclosed for querying, retrieval, and presentation of data. A data analytic system can enable a user to provide input, through a device to query data. The data analytic system can identify the semantic meaning of the input and perform a query based on the semantic meaning. The data analytic system can crawl multiple different sources to determine a logical mapping of data for the index. The index may include one or more subject areas, terms defining those subject areas, and attributes for those terms. The index may enable the data analytic system to perform techniques for matching terms in the query to determine a semantic meaning of the query. The data analytic system can determine a visual representation best suited for displaying results of a query determined by semantic analysis of an input string by a user.