Graph Search Query Metadata for Web Content Relevance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current search systems struggle to effectively identify and rank web resources based on complex queries due to their inability to interpret and utilize the underlying data models of graphical content items, which are often not accessible or interpretable.
Innovation Solution
The implementation of graph search queries that allow users to visually represent search queries using nodes and edges, generating metadata that can be compared to content metadata sets, enabling the search system to account for underlying data models and relationships, thereby improving relevance and ranking of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional text-based search queries are used, then the search system can process simple keyword matches, but it cannot effectively interpret complex relationships and underlying data models of graphical content items
Solution Approach 1:
The patent transitions from one-dimensional text-based queries to two-dimensional graph-based queries with nodes and edges. This dimensional expansion enables the representation of complex relationships between search elements, allowing the system to interpret both simple keywords and complex relational structures within a unified query framework.
Solution Approach 2:
The search query is segmented into discrete graph elements (nodes representing entities and edges representing relationships). This segmentation allows the system to process and interpret individual components and their relationships separately, improving the precision of complex query interpretation while maintaining flexibility through modular graph construction.
2Reliability
If the search system attempts to analyze underlying data models of graphical content items, then relevance identification improves, but the complexity of processing increases due to inaccessibility of data models
Solution Approach 1:
The patent introduces graph search query metadata as an intermediary representation that bridges the gap between accessible query information and inaccessible underlying data models. This metadata structure enables the system to analyze relationships and content without direct access to proprietary data models, improving reliability while controlling processing complexity through standardized metadata formats.
Solution Approach 2:
Instead of directly accessing underlying data models, the system creates and processes copies in the form of graph search query metadata. This copying approach allows comprehensive analysis of search relationships without the complexity of directly interfacing with inaccessible data models, as the metadata serves as a complete but simplified representation.
3Ease of operation
If graph search queries with visual representation tools are provided, then user ability to specify relationships improves, but the complexity of the search interface increases
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically generates graph search query metadata from user interactions with the visual interface. Users simply select elements and relationships through the tool, and the system handles the complex metadata generation and processing automatically, improving ease of operation while masking interface complexity through automation.
Solution Approach 2:
The visual graph search query tool serves as an intermediary layer between the user and the complex metadata processing system. It provides an intuitive interface for specifying relationships while the underlying metadata generation handles the complexity, allowing users to benefit from enhanced relationship specification capability without directly confronting the complexity of the processing mechanisms.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating search query metadata for a graph search query for use in selecting web pages relevant to the graph search query. In one aspect, a method includes receiving a graph search query specifying user-selected graph search elements; generating graph search query metadata representing the graph search elements of the graph search query and relationships of the graph search elements; comparing the graph search query metadata to content metadata sets, wherein each content metadata set represents content elements of a content item presented on a respective web resource and relationships of the content elements; determining similarity scores between the content metadata sets and the graph search query metadata based on the comparison; and selecting web resources on which the content items are presented based on the similarity scores of the respective content metadata sets.