Hierarchical Text Record Selection for Trademark Goods Lists
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Solution Overview
Problem
The complexity of selecting the correct list of goods and services for trademark registration, particularly in international applications, is hindered by the need for professional knowledge and varying trademark laws across countries, and existing systems lack automated selection of goods and services.
Innovation Solution
A method for generating a list of text records using a hierarchical classifier with multiple levels of nesting, enabling automated selection and formation of goods and services through a multi-level hierarchical database, using associated text records and delimiters for accurate listing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually search the entire Nice Classification list to select goods and services, then they can find relevant entries, but the process becomes complex and time-consuming requiring professional knowledge
Solution Approach 1:
The classification system is segmented into multiple hierarchical levels (class level, section level, group level, subsection level) allowing users to navigate from general to specific categories systematically, reducing the complexity of searching through the entire classification list
Solution Approach 2:
The system introduces an intermediary hierarchical structure between the user and the detailed goods/services list. Users interact with high-level classes and sections first, then progressively drill down to specific groups and subsections, making the selection process more manageable and less complex
2Reliability
If users manually review the entire goods and services classifier to select appropriate items, then they can ensure comprehensive coverage, but the time required increases significantly
Solution Approach 1:
The system performs preliminary organization of goods and services into a pre-structured hierarchical database with defined relationships between classes, sections, groups, and subsections. This preliminary structuring enables faster retrieval and selection without requiring users to review the entire classification manually
Solution Approach 2:
The system adds hierarchical dimensionality to the classification data, organizing it across multiple levels (class→section→group→subsection) rather than presenting it as a flat list. This dimensional organization allows users to navigate efficiently and ensures comprehensive coverage by systematically exploring each level
3Adaptability or versatility
If a converter is created for the ICGS classifier to account for country-specific enforcement regulations, then international trademark applications can be supported, but the system still lacks automated selection of goods and services
Solution Approach 1:
The hierarchical classification system is designed with universal applicability across different countries and classification systems. The multi-level structure (classes, sections, groups, subsections) can accommodate various national classification requirements while maintaining a consistent organizational framework that enables automated processing
Solution Approach 2:
The system replaces the manual mechanical process of selecting goods and services with an automated electronic system. The processor automatically retrieves and formats the list of goods and services based on selected classes and sections, eliminating the need for manual review and formatting while maintaining adaptability to different classification systems
Data Source
AI summary
In a preferred embodiment claimed a method for generating a list of text entries executed by the processor of a computer device, containing the following steps: forming request to a database of the text records of a hierarchical classifier with several levels of nesting, and the database contains at least a set of the associated text records, wherein each of the associated text records associated with at least one first sign of connectivity, and each first sign of connectivity corresponds to one of the subheadings, and each unique text record is associated with a unique title, wherein each unique title contains a list consisting of at least plurality of the unique subheadings; and the unique text records are associated in the database with one of the mentioned unique subheadings to obtain a set of associated text records; extracting multiple associated text records from the database; forming a list from the extracted text records, wherein the text records are written in the list using a delimiter.