Product Semantics Search System Using Tag-Based Criteria
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Solution Overview
Problem
Existing product search methods are cumbersome and inefficient due to manual keyword entry and limited selection criteria, often requiring multiple searches to find a perfect match, especially when the 'look, feel, and touch' of a product in a shop do not align with online results.
Innovation Solution
A system that determines product semantics based on associated tags, using RFID or similar technologies, to generate search criteria that can be fine-tuned for more efficient and user-friendly internet searches, incorporating multiple product characteristics and allowing user input for modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual keyword entry is used for product search, then the search can be performed with basic functionality, but the search process becomes cumbersome and inefficient
Solution Approach 1:
The system enables self-service by automatically extracting product semantics and generating search criteria from product tags without requiring manual keyword entry. The product search device autonomously processes tag information, determines product semantics, and formulates search queries, eliminating the need for users to manually input search terms while improving both efficiency and convenience.
Solution Approach 2:
The system performs preliminary action by pre-determining product semantics and generating search criteria before the actual search execution. The product search device prepares comprehensive search parameters in advance based on product tag analysis, so that when the search is initiated, all relevant criteria are already formulated, streamlining the search process and improving efficiency.
2Adaptability or versatility
If restricted product selection criteria are used, then the search system remains simple, but the search becomes inflexible and requires multiple iterations
Solution Approach 1:
The system achieves universality by creating a multi-functional product search device that can handle diverse product types and search requirements through a unified approach. The device determines product semantics from tags and generates comprehensive search criteria that adapt to different products and user needs, providing flexible search capabilities across various product categories without requiring separate specialized systems for each product type.
Solution Approach 2:
The system implements parameter changes by dynamically adjusting search criteria based on determined product semantics. The product search device modifies search parameters such as product properties, specifications, and characteristics according to the semantic analysis of product tags, enabling flexible adaptation to different search requirements while maintaining a consistent system architecture.
3Measurement precision
If multiple searches are performed to find the perfect match, then the search coverage increases, but the time and effort required increases significantly
Solution Approach 1:
The system performs preliminary action by pre-generating comprehensive search criteria including multiple product characteristics, properties, and specifications before executing the search. The product search device formulates complete and precise search queries in advance based on product semantics, ensuring that a single search operation covers all relevant aspects and eliminates the need for multiple iterative searches, thereby reducing search time while maintaining high matching accuracy.
Solution Approach 2:
The system implements feedback by using product semantics determination results to continuously refine and optimize search criteria. The product search device analyzes the outcomes of searches and adjusts the semantic interpretation and search parameter generation accordingly, improving matching accuracy over time while reducing the number of searches needed to find the perfect match.
Data Source
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AI summary
The present invention relates to a system for searching a product (on the internet) where the product is similar to a first product. This system first comprises a product semantics determining part that is adapted to determine the semantics of the first product based on a tag associated to this first product; and further a product semantics interpreting part that is adapted to interpret the product semantics of the first product and generate at least one search criterion corresponding to the product semantics of the first product.