Knowledge Search System Using Data Graph Entity Relationships
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Solution Overview
Problem
Conventional search engines face challenges in providing accurate and efficient search results due to incorrect or incomplete keywords, misspellings, and gaps between user queries and online data, leading to a time-consuming process for end users and potential lost business opportunities for merchants.
Innovation Solution
A knowledge search system that employs natural language processing, customizable entity types, and relationship types to enhance search experiences, allowing merchants to manage and centralize data across multiple platforms, providing intuitive search results and auto-completion features, and enabling updates to be synchronized across different publisher systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines use keyword-based searching, then search functionality is provided, but search accuracy deteriorates due to incorrect keywords, misspellings, and gaps between queries and online data
Solution Approach 1:
The patent introduces an intermediary layer between the user's natural language query and the search engine's keyword processing. This intermediary includes autocomplete suggestions, query reformulation algorithms, and semantic interpretation mechanisms that bridge the gap between user intent and searchable data, thereby improving search accuracy without relying solely on exact keyword matches
Solution Approach 2:
The patent replaces the traditional mechanical keyword-matching system with natural language processing and semantic analysis mechanisms. Instead of requiring exact keyword correspondence, the system uses AI-driven interpretation to understand user intent, handle misspellings, and match queries with relevant data based on meaning rather than literal text comparison
2Adaptability or versatility
If merchants publish information across multiple platforms, then market reach is expanded, but data management complexity increases and uniformity deteriorates
Solution Approach 1:
The patent creates a universal data management system that serves multiple functions: centralized data storage, automated distribution across platforms, and consistent formatting. This multi-functional platform allows merchants to manage all their publication channels through a single interface, eliminating the need for separate management systems for each platform while maintaining data uniformity across all channels
Solution Approach 2:
The patent merges multiple data management functions and multiple platform interactions into a single integrated system. By combining data storage, processing, distribution, and synchronization capabilities into one unified platform, the system reduces management complexity while enabling expanded market reach across multiple channels
3Ease of operation
If search results are generated without guidance, then search freedom is maintained, but search time increases and user experience deteriorates
Solution Approach 1:
The patent applies preliminary action by providing autocomplete suggestions and predicted search results before the user completes their query. The system anticipates user intent and pre-generates relevant results or suggestions, allowing users to quickly select from predefined options rather than typing complete queries, thereby reducing search time while maintaining ease of use
Solution Approach 2:
The patent implements feedback mechanisms where the system analyzes user search behavior, click patterns, and interaction data to continuously improve result ranking and relevance. This feedback loop allows the system to learn from user preferences and provide increasingly accurate, personalized results, improving search experience while reducing the time needed to find relevant information
Data Source
AI summary
A system and method to manage data associated with a merchant system to provide in response to a search query from an end user system. The system and method to generate, in a data graph associated with a merchant system, a first entity type including a first data field storing a first data value corresponding to the merchant system. A second entity type comprising a second data field storing a second data value corresponding to the merchant system is generated in the data graph. A relationship type between the first entity type and the second entity type is established. A first update to the first data value of the first entity type is generated. In view of the relationship type, a second update to the second data value of the second entity type is generated. The first update of the first entity type and the second update of the second entity type are stored in the data graph.