Adaptive Query Filters From Search Result Content
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Solution Overview
Problem
Existing search systems require users to manually generate or rely on hardcoded filters, which often necessitate expert knowledge and are ineffective in dynamically adapting to the ever-changing resource landscape on the Internet, leading to incomplete or inaccurate search results.
Innovation Solution
A search engine system that automatically learns and generates query filters from the content of responsive resources, using keyword extraction and diversity criteria to provide tailored filters that adapt to user needs and available results, enhancing search engine performance and reducing human effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual filter generation or hardcoded filters are used, then filter effectiveness can be maintained with expert knowledge, but device complexity and user effort increase significantly
Solution Approach 1:
The search engine automatically generates and refines filters by analyzing search queries and results without requiring user input or expert programming. The system serves itself by learning from usage patterns and dynamically creating filters that adapt to changing search needs.
Solution Approach 2:
The system continuously monitors user interactions with search results and uses this feedback to refine and improve filter effectiveness. User behavior data is analyzed to identify successful filtering patterns and automatically update the filter generation mechanism.
2Reliability
If hardcoded filters are used, then initial filter performance can be achieved, but adaptability to dynamic resource changes deteriorates
Solution Approach 1:
The filter generation system is dynamic and adapts to changing search landscapes in real-time. Filters are continuously updated based on current search queries, results, and user behavior patterns, allowing the system to respond to emerging search trends and resource changes.
Solution Approach 2:
The system performs preliminary analysis of search queries and results to proactively generate filters before users need them. By anticipating user needs based on patterns in the data, the system prepares relevant filters in advance rather than reacting to user requests.
3Adaptability or versatility
If automatic filter generation from resource content is implemented, then adaptability to dynamic resources improves, but device complexity increases
Solution Approach 1:
The system extracts relevant filtering information from the content of search results and uses this extracted data to generate filters. By pulling out meaningful features from the results themselves, the system creates adaptive filters without requiring complex external processing or manual configuration.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing filters from resource content. In one aspect, a system receives data identifying a set of resources that are determined to be responsive to a search query and extracts a set of keywords from the contents of the resources and related queries. The keywords are processed according to candidate selection criteria, and a set of candidate query filters are determined. The candidate filters may be used to filter the resources that are responsive to the query.