Ontology-Based Domain Name Suggestion Engine
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Solution Overview
Problem
Current search and advertising technologies fail to effectively display concept-based results that are relevant to search terms, domain names, and targeted advertising, as they rely on outdated methods that do not account for the complexities of human memory and the semantic relationships between concepts.
Innovation Solution
A method that receives information, establishes individual concepts, identifies related classes based on attributes, and calculates results by determining the most closely related concepts within these classes, using an ontology-based system with Input Knowledge Agents, Results Engines, Databases, and Output Knowledge Agents to display concept-based results, including search results, domain names, and targeted advertising suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search and advertising methods are used, then system simplicity is maintained, but relevance and user satisfaction of results deteriorate
Solution Approach 1:
The patent segments the search process into distinct functional modules: a search engine that processes queries, an ontology database that stores structured knowledge, a concept matching engine that performs semantic analysis, and an advertising system that delivers targeted results. This modular segmentation allows each component to specialize in specific tasks, improving overall relevance while managing complexity through distributed functionality.
Solution Approach 2:
The patent introduces an ontology-based concept matching engine as an intermediary between traditional search queries and result delivery. This intermediary layer translates user queries into semantic concepts, matches them against the ontology database, and retrieves relevant results based on conceptual relationships rather than simple keyword matching, thereby improving relevance without requiring complete system redesign.
2Measurement precision
If concept-based semantic analysis is implemented, then accuracy of domain name suggestions improves, but processing time increases
Solution Approach 1:
The patent pre-processes and structures vast amounts of information into an ontology database during off-peak periods, organizing knowledge into hierarchical concept structures with defined relationships. This preliminary action creates a ready-to-query semantic framework that accelerates real-time concept matching during actual searches, reducing processing time while maintaining high accuracy.
Solution Approach 2:
The patent applies concept-based semantic analysis selectively to specific parts of the search process, particularly in matching user queries with domain name suggestions and advertising content, rather than processing entire result sets uniformly. This localized application of semantic analysis optimizes accuracy for critical decision points while minimizing overall processing overhead.
3Reliability
If traditional keyword-based advertising is used, then ease of implementation is maintained, but effectiveness and user relevance deteriorate
Solution Approach 1:
The patent transforms advertising from simple keyword-based delivery to a multi-parameter system that considers user query semantics, concept relationships, user profile data, and contextual relevance. By changing the parameters used for ad selection and delivery, the system achieves higher effectiveness and user relevance while the modular architecture manages the increased complexity through organized parameter handling.
Data Source
AI summary
Methods and systems of the present invention allow for displaying suggested concept-based results. An exemplary method may comprise the steps of receiving a combination domain name and top level domain (TLD), determining from ontological calculations suggested TLDs related to the concept of the combination and displaying the suggested combination of the domain name with suggested TLDs.