Personalized Search via Group Content Mixing
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Solution Overview
Problem
Current search engines struggle to provide personalized and relevant search results, as they rely on static and dynamic ranking methods that do not adequately account for individual user preferences and relationships, leading to varying levels of relevance and satisfaction among users.
Innovation Solution
The system combines a user's personal content with related users' content to generate personalized search results by leveraging group membership, using techniques such as groupized ranking, smart splitting, and group query expansion, which involves generating individual personalization scores, distributing search queries for parallel evaluation, and broadening search queries based on related queries from group members.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static and dynamic ranking methods are used to organize search results, then search results can be systematically presented, but the results do not adequately reflect individual user preferences and relationships
Solution Approach 1:
The system pre-establishes user profiles containing personal data, interests, and relationship information before search queries are submitted. This preliminary preparation enables rapid personalization of search results without adding complexity to the actual search operation, resolving the contradiction between systematic presentation and personalization capability.
Solution Approach 2:
The search result ranking system transitions from static conventional methods to a dynamic model that incorporates real-time user profile data, relationship graphs, and interaction patterns. The ranking algorithms adaptively adjust based on user-specific factors, enabling both systematic organization and personalized adaptation simultaneously.
2Device complexity
If conventional search ranking methods are used, then processing complexity remains manageable, but search results lack relevance to individual users and their relationships
Solution Approach 1:
The search system is divided into independent modules: user profile analysis component, relationship graph processing component, query expansion component, and result ranking component. Each module handles specific tasks separately, making the complex personalization process manageable while improving result relevance through specialized processing.
Solution Approach 2:
A user profile acts as an intermediary between the raw search query and the final results. The profile contains pre-processed user data, interests, and relationship information that mediates the interaction between query and results, enhancing relevance without requiring the entire system to process all personalization data in real-time.
3Adaptability or versatility
If search results are personalized based on individual user data only, then individual preferences are addressed, but the system misses opportunities to leverage shared interests and relationships among users
Solution Approach 1:
The system merges individual user profiles with relationship graph data to create an enhanced personalization model. User-specific interests are combined with group interests derived from connected users, allowing the system to leverage both individual preferences and shared relationships simultaneously for more comprehensive result personalization.
Data Source
AI summary
The claimed subject matter provides a system and/or a method that facilitates generating a personalized query result for a specific user. An interface can receive at least one of a portion of a text query to be searched or a portion of personalized content related to a user that submits the portion of the text query. A personalization component can combine the portion of personalized content related to the user with a portion of personalized content related to one or more disparate users to create group personalized content, wherein the group personalized content is compared with the portion of the text query to identify a relationship there between to generate a personalized query result in accordance with the relationship.