Query Enhancement System Using Implicit Data Mapping
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Solution Overview
Problem
Conventional search engines often return inaccurate results due to users entering terms that are not recognized by manufacturers, leading to overwhelming amounts of irrelevant data that complicate access to the desired product.
Innovation Solution
A query enhancement system that associates user terms with manufacturer-identified terms by analyzing user interactions and data from networked marketplaces, allowing it to return search results based on manufacturer-identified terms even when users enter different or slang terms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional search engines return all results matching user-entered terms, then the system maintains simplicity in search processing, but the user is overwhelmed by irrelevant data and cannot easily access the desired product
Solution Approach 1:
The patent introduces an intermediary component that sits between the user's search query and the search engine results. This intermediary analyzes user implicit data (clicks, views, purchases) to identify patterns and filter results, acting as a mediator that translates user behavior into refined search outcomes without requiring the user to manually filter overwhelming result sets
Solution Approach 2:
The system implements feedback loops where user interactions with search results (clicks, views, purchases) are continuously collected and analyzed. This feedback is used to dynamically adjust and refine future search results, creating a self-improving system that learns from user behavior to progressively reduce irrelevant results while maintaining ease of access to desired products
2Adaptability or versatility
If the search engine uses only manufacturer-identified terms, then the system maintains precision in product identification, but users cannot search using their own terminology or slang terms
Solution Approach 1:
The patent transforms the search parameter space by mapping user terms (including slang and informal terminology) to manufacturer-identified terms through analysis of user implicit data. This parameter transformation allows the system to accept diverse user input while maintaining precise product identification by translating queries into the manufacturer's terminology framework
Solution Approach 2:
An intermediary mapping mechanism is introduced that translates between user terminology and manufacturer terminology. This mediator analyzes patterns in user implicit data to establish correlations between user terms and manufacturer terms, enabling the system to accept flexible user input while maintaining precise product identification through term translation
3Reliability
If the system analyzes user implicit data from networked marketplaces, then the system improves search relevance by associating user terms with manufacturer terms, but the system complexity increases
Solution Approach 1:
The system implements self-service mechanisms where user implicit data automatically feeds into the term association process without requiring manual intervention. The system autonomously collects, analyzes, and applies user behavior data to refine search queries, reducing the need for complex manual configuration while maintaining high search relevance through automated learning from user interactions
Data Source
AI summary
Systems and methods are disclosed for enhancing user queries. In one embodiment, a method includes receiving user data from a plurality of users in respective user sessions where the user data for each user includes at least one manufacturer-identified term for a product and at least one user term for the product, associating the user term for the product and the manufacturer-identified term for the product in response to receiving the user term and the manufacturer-identified term within a user session from a threshold number of users, and returning search results based on the associated manufacturer-identified term in response to receiving a search query that includes the user term.