Multi-source search interface with contextual launch
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current search technologies fail to efficiently suggest relevant queries and rank search results across multiple content sources, and they lack the ability to provide contextual launch functionality, leading to suboptimal user experience in multi-source search environments.
Innovation Solution
A multi-source search interface that evaluates user signals to identify search intent and content preferences, formulates query suggestions, ranks search results based on relevancy, and exposes contextual launch functionality by embedding links to relevant applications within search results, allowing for efficient querying and result presentation across various content sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multi-source search is implemented to search across multiple content sources, then search coverage and content variety are improved, but system complexity and computational overhead increase
Solution Approach 1:
The patent segments the multi-source search system into distinct functional modules: query suggestion formulation module, search result ranking module, and contextual launch module. Each module handles specific tasks independently, managing complexity through functional decomposition while maintaining comprehensive multi-source search capability across files, emails, contacts, social networks, and web content.
Solution Approach 2:
The patent introduces an intermediary search interface that mediates between the user and multiple content sources. This intermediary layer processes queries, coordinates searches across diverse sources, and presents unified results, thereby managing system complexity while enabling broad search coverage across multiple platforms and content types.
2Measurement precision
If query suggestions are formulated based on user signals and search intent, then search relevance and user experience are improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-processing and analyzing user signals (search history, usage patterns, preferences) to establish user profiles and intent models before actual search queries are submitted. This preliminary analysis enables rapid query suggestion formulation in real-time, improving search relevance without adding significant processing delay to the actual search operation.
3Measurement precision
If search results are ranked based on multiple factors including user preference and relevancy, then result accuracy and user satisfaction are improved, but computational complexity increases
Solution Approach 1:
The patent employs parameter changes by dynamically adjusting ranking weights and thresholds based on user preferences, search context, and content source characteristics. The system modifies relevance parameters and ranking criteria in real-time to optimize result accuracy for different user needs and search scenarios, managing computational complexity through adaptive parameter adjustment rather than complex algorithms.
4Ease of operation
If contextual launch functionality is embedded in search results, then user convenience and operational efficiency are improved, but interface complexity increases
Solution Approach 1:
The patent extracts contextual launch functionality as a separate, optional feature within the search interface. Rather than integrating complex launch mechanisms throughout the entire interface, the system provides contextual launch options (such as quick-action buttons or launch links) only in relevant search results, thereby improving user convenience while minimizing overall interface complexity through selective feature deployment.
Data Source
AI summary
One or more techniques and/or systems are provided for query suggestion formulation for multi-source queries, for ranking multi-source search results, and/or for exposing contextual launch functionality through multi-source search results of a multi-source search interface. In an example, a query suggestion may be provided for a partial search query based upon an implied content source that corresponds to a search intent of a user (e.g., an intent to view videos, as opposed to images, of houses). In another example, relevancy ranks may be assigned to content sources based upon a content type preference of a user, and search results may be provided from content sources having relevancy rankings above a relevancy threshold. In another example, links to applications and/or execution contexts may be embedded within search results so that applications may be launched into contextually aware states from the search results.