User-Specific Search Refiners for Content Filtering
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Solution Overview
Problem
Users face difficulties in efficiently searching for content items in applications like email due to the overlap of keywords among desired and undesired content items, leading to time-consuming and frustrating searches.
Innovation Solution
A system and method that utilize user-specific and tenant/entity-specific refiners, based on long-term aggregated data and contextual information, to filter search results by generating and selecting topic-based, dynamically determined refiners that analyze content items and provide relevant filters to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If keyword-based search is used to find content items, then the search can be performed using simple terms, but many undesired content items are returned due to keyword overlap
Solution Approach 1:
The search result filtering process is segmented into multiple stages: initial keyword-based search followed by refiner-based filtering. The refiners segment the broad search results into more precise subsets based on user-specific criteria such as content categories, authors, dates, and other attributes, thereby improving accuracy while maintaining operational simplicity.
Solution Approach 2:
Refiners act as intermediary elements between the user's keyword search and the final search results. These refiners mediate the search process by applying additional filtering criteria that bridge the gap between simple keyword matching and precise result retrieval, reducing keyword overlap issues while maintaining ease of use.
2Productivity
If user-specific refiners are generated and applied to filter search results, then search efficiency is improved, but the system complexity increases
Solution Approach 1:
User-specific refiners are generated in advance based on analysis of user behavior, content preferences, and interaction patterns. This preliminary action allows the system to have filtering criteria ready before searches are executed, improving search efficiency without adding complexity during the actual search operation. The refiners are pre-computed and stored for rapid application.
Solution Approach 2:
The system automatically generates and updates refiners based on user behavior data without requiring manual configuration. This self-service approach allows the system to adapt to individual user needs while maintaining a manageable level of complexity through automated processes rather than manual system configuration.
3Measurement precision
If refiners are generated based on long-term aggregated data and contextual information, then the relevance of search results to user interests is improved, but the data processing requirements increase
Solution Approach 1:
The system performs data aggregation and refiner generation in advance, during periods when user activity is lower. By pre-processing and storing aggregated user behavior data and contextual information, the system reduces the computational burden during actual search operations, improving result relevance while managing energy consumption through temporal distribution of processing tasks.
Data Source
AI summary
The present application describes a system and method for searching for content items in an application executing on a computing device. In order to increase the efficiency of the search, the present disclosure provides a refiner that is used to filter or otherwise refine search results. The refiner is user-specific and/or tenant/entity-specific. The refiner may be based on long-term aggregated data and/or contextual information associated with the user.