Knowledge Graph Entity Query for Search Result Classification
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Solution Overview
Problem
Current search engines produce unclear, disordered, incomplete, or inaccurate search result pages, making it difficult for users to quickly find useful information.
Innovation Solution
An information query method and apparatus that identifies a target entity in a query word, determines its globally unique identifier in a knowledge map, and displays search results in an entity detail card based on entity type priority, including attribute values and related entities, with optional extended type tags and hot news integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional search engines are used to retrieve information, then users can obtain web page content and links related to search keywords, but the search result page classification is not clear and the recommended content is disordered, incomplete or inaccurate
Solution Approach 1:
The patent introduces a knowledge graph as an intermediary data structure between the search engine and user. The knowledge graph organizes entities, attributes, and relationships in a structured manner, serving as a mediator that transforms unstructured search results into classified, organized information presentations with clear categories and hierarchical relationships.
Solution Approach 2:
The patent segments search results into distinct entity types (person, organization, location, etc.) and further divides them into hierarchical categories based on the knowledge graph structure. Each entity is presented with its attributes and relationships separately organized, making the previously disordered content systematically classified and easier to navigate.
2Loss of information
If more search results are provided to ensure completeness, then the information becomes more comprehensive, but the search result page becomes more disordered and harder to navigate
Solution Approach 1:
The patent adds a new dimensional organization to search results by introducing entity types and hierarchical categories as additional classification dimensions. Instead of presenting all results in a single flat list, the system organizes them across multiple dimensions (entity type, category hierarchy, attributes, relationships), allowing comprehensive information to be presented in an structured, navigable format.
3Ease of operation
If search results are organized by multiple entity types and categories, then the classification becomes clearer, but the system complexity increases
Solution Approach 1:
The patent creates a universal knowledge graph framework that can handle multiple entity types (person, organization, location, etc.) and relationships through a unified data structure. This multi-functional system uses standard schemas and ontologies that can accommodate diverse information types without requiring separate processing mechanisms for each entity type, thereby managing complexity through standardization.
Data Source
AI summary
Disclosed is an information query method and apparatus. The method includes: obtaining a query word input by a user through a terminal, identifying a target entity in the query word and determining a globally unique identifier (GUID) of the target entity for a knowledge map; determining a target entity type corresponding to the target entity according to a corresponding relationship between an entity and the entity type. The target entity type is used to indicate the target attribute and/or target entity relationship to be queried of the target entity; according to the GUID and an identifier of the target attribute and/or an identifier of the target entity relationship, querying an attribute value and/or a related entity corresponding to the identity of the target attribute and/or an identifier of the target entity relationship in the knowledge map; returning a search result to the terminal.