Interactive Search Query Refinement With Collaborator Units
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Solution Overview
Problem
Existing internet search systems fail to accurately determine user intent from short search queries, leading to time-consuming and frustrating searches, and often disseminate user data without user knowledge.
Innovation Solution
A computer-implemented system with a collaborator unit that accesses reference and search term databases to match user inputs, refine queries, and generate targeted search results, incorporating user profile, publisher, and product data to provide precise and minimally invasive search outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search engines process short search queries using basic algorithms, then the system complexity remains low, but the search accuracy and ability to determine user intent deteriorates
Solution Approach 1:
The system segments the search process into multiple stages: initial query processing, iterative refinement cycles with collaborator units, and final result generation. Each stage handles specific aspects of query understanding and refinement, allowing complex analysis to be distributed across modular components rather than concentrated in a single monolithic system.
Solution Approach 2:
The system performs preliminary actions by pre-processing queries through multiple collaborator units before final result generation. Each collaborator unit prepares refined versions of the query in advance, and the system selects from these pre-prepared options, reducing the complexity of real-time decision-making while maintaining high accuracy.
2Measurement precision
If search systems collect and analyze extensive user data to improve search results, then the search accuracy improves, but the user privacy and data security deteriorates
Solution Approach 1:
The system applies local quality by allowing different collaborator units to access different types of user data based on their specific functions. Each unit receives only the minimum necessary data for its purpose, and user profile information is selectively applied only where relevant to the specific search context, rather than universally across all processing stages.
Solution Approach 2:
User profile data acts as an intermediary layer between the raw search query and the final results. The collaborator units reference this intermediate user context information to refine queries without directly exposing or transmitting sensitive user data across the system, thereby maintaining privacy while improving accuracy.
3Measurement precision
If users enter multiple refined search queries to find accurate results, then the search accuracy improves, but the time required for searching deteriorates
Solution Approach 1:
The system performs preliminary actions by having multiple collaborator units generate refined query versions in advance before the user needs to review results. This pre-computation of multiple query refinements eliminates the need for users to iteratively enter multiple queries, as the system has already performed the iterative refinement work beforehand.
Solution Approach 2:
The system implements feedback mechanisms where collaborator units continuously refine queries based on initial results and user profile information, then present improved results back to the user. This automated feedback loop replaces manual iterative searching, maintaining high accuracy while reducing the time users must spend entering multiple queries.
Data Source
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AI summary
A computer-implemented system for interactive queries and searches is provided. The system may include a reference data database including reference data, a search term database including search terms, and a collaborator unit. The collaborator unit may receive a user input inputted into an interaction space of a user device and may compare and match the user input to the search terms to define a first query input. The collaborator unit may associate the first query input with portion(s) of the reference data to generate an output response. The collaborator unit may receive an additional user input and may compare and match the additional user input to the search terms to define a refined query input. The collaborator unit may associate the refined query input with portion(s) of the reference data and with the first output response to generate another output response.