Service Graph for Location-Based Search Across Heterogeneous Data
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Solution Overview
Problem
Current location-based services face challenges in scalability, response speed, and robust query support when dealing with multiple heterogeneous data sources, as federated searches struggle to maintain performance and accuracy with increasing information sources, often restricting query capabilities and facing availability issues.
Innovation Solution
A system and method for executing location-based queries across multiple heterogeneous data sources and services using a Service Graph, which selects and prioritizes relevant sources, generates an execution strategy, and merges results in a standardized form, leveraging machine learning and feedback loops for efficient operations and quality results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If federated searches are used to access multiple heterogeneous data sources, then information coverage and data variety are improved, but response speed and system reliability deteriorate
Solution Approach 1:
The system segments the federated search process into distinct phases: query planning (selecting relevant data sources), query execution (parallel searching across selected sources), and result merging (combining and deduplicating results). This segmentation allows optimization at each stage, particularly through parallel execution of independent search operations across multiple data sources, thereby maintaining response speed while accessing heterogeneous data.
Solution Approach 2:
The system performs preliminary actions by pre-evaluating and selecting the most relevant data sources before executing the actual search. The query planner analyzes the query semantics and data source characteristics in advance to identify optimal sources, avoiding unnecessary searches across all available heterogeneous data sources. This preliminary selection significantly reduces response time while maintaining comprehensive information coverage.
2Loss of information
If more heterogeneous data sources are integrated, then information completeness is improved, but system complexity and query execution difficulty worsen
Solution Approach 1:
The system introduces an intermediary layer consisting of the query planner and result merger that mediates between the user query and multiple heterogeneous data sources. The query planner translates diverse query types into source-specific search operations, while the result merger standardizes and integrates results from different sources with varying schemas and formats. This intermediary layer abstracts the complexity of heterogeneous data integration, allowing the system to maintain information completeness without proportionally increasing system complexity.
Solution Approach 2:
The system implements universal components that handle multiple functions: the query planner supports various query types (spatial, temporal, attribute-based searches) and adapts to different data source schemas, while the result merger provides unified result formatting regardless of source heterogeneity. This multi-functionality allows the system to integrate numerous heterogeneous data sources without linearly increasing complexity, as the same core components serve multiple data sources and query types.
3Adaptability or versatility
If comprehensive query support is provided across multiple data sources, then search capability is improved, but query execution time and resource consumption worsen
Solution Approach 1:
The system dynamically adapts the query execution strategy based on query characteristics, data source availability, and performance metrics. The query planner dynamically selects which data sources to search based on query semantics and source relevance, rather than statically searching all sources. The result merger dynamically filters and prioritizes results from different sources based on their quality and relevance. This dynamic behavior allows the system to provide comprehensive query support while minimizing execution time by avoiding unnecessary searches.
Data Source
AI summary
System and methods are provided for executing queries across multiple services and data sources using a Service Graph. The Service Graph is customizable and trainable using continuous feedback loops among the various components of the Service Graph. The Service Graph is configured to select at least one data source or at least one location service from a plurality heterogeneous data sources and location services, generate an execution strategy for searching the at least one location service or the at least one data source, and provide the results generated as a result of the execution strategy.