Map-Based Visual Autocompletion for Cognitive Geospatial Queries
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Solution Overview
Problem
Existing natural language processing systems struggle to accurately and flexibly handle geospatial queries involving vague or cognitive regions, as users often find it difficult to translate their conceptual understanding of space into precise geographic definitions, leading to unsatisfactory search processes.
Innovation Solution
A system that provides visual autocompletion through a map widget, allowing users to select geospatial data points and specify regions, with features like hexbin-based previews, detailed base maps, and coverage metrics to refine queries, supporting both named and cognitive regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users translate vague conceptual knowledge into concrete descriptions for geospatial queries, then query precision improves, but the search process becomes difficult and unsatisfactory when user input does not match the underlying data structure
Solution Approach 1:
The patent introduces an intermediary system that translates between vague user concepts and precise data structures. The system uses natural language processing to interpret user intent, matches it with relevant data sources, and presents refined query options. This mediator layer bridges the gap between imprecise user input and structured data requirements, maintaining both ease of use and query precision.
Solution Approach 2:
The system performs preliminary actions by pre-processing and structuring data before user queries are submitted. It anticipates user needs by organizing data in multiple representations (spatial, temporal, categorical) in advance, so when users provide vague input, the system can quickly match it with pre-organized data structures without requiring users to formulate perfectly precise queries.
2Reliability
If natural language interfaces provide traditional autocompletion, then users can generate valid queries with visual cues, but the system does not provide a natural and flexible mode of spatial exploration that aligns with vague ways people conceptualize space
Solution Approach 1:
The patent implements dynamic autocompletion that adapts to user needs in real-time. Instead of static suggestions, the system dynamically generates query options based on the user's current input, the data context, and inferred spatial intent. The autocompletion interface evolves as users interact with it, providing increasingly refined suggestions that balance structural validity with spatial exploration flexibility.
Solution Approach 2:
The system creates a universal query interface that handles multiple types of spatial concepts (named locations, vague regions, relative positions) through a single unified mechanism. This multi-functional interface can interpret and respond to various forms of spatial expression, making it adaptable to different user mental models while maintaining reliable query generation.
3Device complexity
If the system supports only named administrative geographies, then query structure is simplified, but it cannot handle arbitrary combinations of geographic regions or cognitive regions that cannot easily be represented in natural language
Solution Approach 1:
The patent segments complex spatial queries into manageable components. Instead of requiring users to specify entire complex regions at once, the system breaks down region specifications into hierarchical levels (country, state, county, custom boundaries) and allows users to combine these segments. This segmentation maintains relative simplicity while enabling versatile region specification through compositional query building.
Solution Approach 2:
The system creates composite query structures that combine multiple region types (administrative boundaries, cognitive regions, data-driven regions) into unified query objects. These composite structures allow arbitrary combinations of different region specifications while maintaining a consistent internal representation, enabling both simplicity and versatility simultaneously.
Data Source
AI summary
A computer system receives a natural language input directed to a data source. In response to receiving the natural language input, and in accordance with a determination that the natural language input specifies an incomplete natural language command directed to the data source, the computer system presents a map widget for selecting geospatial data points from the data source. The map widget includes a map having a plurality of predetermined geographic regions. The computer system receives user specification of a user-defined region in the map included in the map widget. In accordance with receiving the user specification and based on a coverage metric computed for the plurality of geographic regions, the computer system selects one or more geographic regions. The computer system completes the natural language command with the selected geographic regions. The computer system generates and displays a map data visualization according to the completed natural language command.