Custom Search Query System with Multi-Engine Rating
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Solution Overview
Problem
Current web search engines lack the ability to store and automatically apply custom user-specified preferences for searching, making it inconvenient for users to limit searches to preferred sites across multiple engines.
Innovation Solution
A method and system that allows users to input and categorize preferred websites, generating customized search queries for multiple search engines like Google, Bing, and Yahoo, while also rating websites based on user interactions, with options to increase ratings through commercial purchases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually write complex custom query strings to search specific sites on multiple search engines, then search scope can be limited to preferred sites, but user convenience deteriorates significantly
Solution Approach 1:
The system performs preliminary action by automatically generating and storing customized query strings with user-specified search sites before actual search execution. Users define their preferred sites once, and the system pre-computes the query templates, eliminating the need for users to manually write complex queries each time they search.
Solution Approach 2:
The system introduces an intermediary layer between the user and multiple search engines. This intermediary automatically manages query construction, site filtering, and search execution across multiple engines, shielding users from the complexity of individual search engine syntax while maintaining precise control over search scope.
2Extent of automation
If no system stores custom user-specified web sites for search limitation, then system simplicity is maintained, but user search preferences cannot be automatically applied
Solution Approach 1:
The system achieves universality by creating a multi-functional platform that combines site preference storage, automatic query generation, multi-engine search coordination, and search result aggregation. This single system handles multiple functions that would otherwise require separate tools, justifying the added complexity through significant automation benefits.
Solution Approach 2:
The system implements self-service by automatically retrieving stored user preferences and applying them to search operations without user intervention. The system autonomously constructs queries, selects appropriate search engines, and retrieves results based on pre-configured site preferences, freeing users from repetitive manual configuration.
3Measurement precision
If suggested sites are displayed based on ratings, then search relevance is enhanced, but system complexity increases due to rating calculation and management
Solution Approach 1:
The system applies feedback by using search interaction data (clicks, dwell time, selections) to continuously update site ratings. This feedback loop refines the relevance measurement over time, with higher-rated sites being prioritized in suggestions, creating a self-improving system that adapts to user behavior patterns.
Solution Approach 2:
The system utilizes parameter changes by dynamically adjusting site rating values based on observed user interactions. As users interact with search results, the rating parameters for different sites are modified, which in turn changes the ordering and visibility of suggested sites, enabling adaptive relevance improvement without complex rule-based systems.
Data Source
AI summary
A method and system are provided for web search customization and web site rating. The system receives user input web sites, stores the web sites in a database, and groups them into user-specified categories. The system further allows users to select one or more web sites for customizing web search and querying the preselected sites using user input keywords. The system further provides the users with options to query a plurality of search engines. All web sites stored within the system are rated in response to the user operations. Each web site has at least a global rating indicating the rating within the system, a category rating indicating the rating within a given category, and a keyword rating indicating the rating for a given keyword. The system provides the users with a list of recommended web sites based on the web sites' ratings.