Personalized Search Query Suggestions Based on User Data
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Solution Overview
Problem
Internet search engines fail to provide personalized query suggestions that leverage user data and service interactions, leading to less relevant search results due to users' unawareness of personalized search features.
Innovation Solution
Implement a system that generates personalized query suggestions based on user data and service interactions, ranking them along with non-personalized suggestions, using content and history-based queries, and displaying them in a tiered arrangement for enhanced relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If personalized query suggestions are generated based on user data and service interactions, then the relevance of search results is improved, but the system complexity increases
Solution Approach 1:
The system segments query suggestions into two distinct categories: personalized suggestions (generated from user data and service interactions) and non-personalized suggestions (generated from general search data). This segmentation allows the system to provide tailored recommendations while maintaining a comprehensive suggestion pool, improving relevance without overwhelming system complexity through modular architecture.
Solution Approach 2:
The patent introduces a suggestion ranking mechanism that acts as an intermediary between the complex personalized suggestion generation process and the user. This mediator ranks and prioritizes suggestions based on multiple factors including personalization level, relevance, and user preferences, simplifying the presentation of complex processed information to the user interface.
2Adaptability or versatility
If multiple types of query suggestions are provided and ranked separately, then the adaptability of the search system is improved, but the complexity of managing and presenting suggestions increases
Solution Approach 1:
The system dynamically adjusts the composition and ranking of query suggestions based on user context, search history, and service interaction data. The ranking algorithm adapts in real-time to user behavior patterns, allowing the system to flexibly prioritize personalized versus non-personalized suggestions without requiring complex manual configuration or static categorization.
3Ease of operation
If personalized query suggestions are integrated with non-personalized suggestions in a unified ranking, then the ease of operation is improved, but the difficulty of determining accurate rankings increases
Solution Approach 1:
The patent employs multiple ranking parameters and scoring mechanisms to evaluate and order query suggestions. Instead of relying on a single complex ranking metric, the system uses adjustable parameters that can weight different factors (personalization score, relevance, user preferences, service context) independently, making the ranking process more manageable and interpretable while maintaining unified presentation for the user.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a query initial input from a user, in response to receiving the query initial input, determining a set of personalized query suggestions based on the query initial input, the set of personalized query suggestions including one or more content-based query suggestions that reflect at least one of user data associated with the user within one or more computer-implemented services and use of the one or more computer-implemented services by the user, and transmitting instructions to display the set of personalized query suggestions to the user.