Incremental Search Engine Selection for Partial Queries
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Solution Overview
Problem
Users face inconvenience in typing full search queries on devices with overloaded keyboards, leading to inefficiencies in obtaining search results, especially when using incremental search with minimal text entry.
Innovation Solution
A method and system that incrementally select and provide relevant search engines by identifying potential full queries and their corresponding metadata, offering direct links to launch queries in relevant search engines, correcting for ambiguous or erroneous input, and ranking queries based on user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If incremental search with minimal text entry is used, then search speed is improved, but search result accuracy deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing search engine metadata, categories, and rankings before the user actually needs to search. When a user enters partial text, the system has already prepared the infrastructure to quickly match and present relevant search engines, enabling fast response without sacrificing accuracy.
Solution Approach 2:
The system continuously monitors user interactions with search results and uses this feedback to refine future search engine selections. By analyzing which search engines users select and how they interact with results, the system improves its accuracy in predicting user intent and selecting appropriate search engines for minimal text queries.
2Ease of operation
If search engines are selected based on partial queries, then ease of operation is improved, but reliability deteriorates
Solution Approach 1:
The system changes the parameters used for search engine selection based on the partial query input. By analyzing the characteristics of the partial query (length, keywords, context) and dynamically adjusting selection criteria, the system maintains high reliability even when users provide incomplete information.
Solution Approach 2:
The system pre-organizes search engines into categories and pre-computes their metadata before user interaction. This preliminary organization allows the system to quickly and reliably match partial queries to appropriate search engines without requiring complete user input.
3Adaptability or versatility
If multiple search engines are provided, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system segments the search engine selection process into distinct manageable components: query analysis, search engine categorization, metadata matching, and result presentation. This segmentation allows the system to handle multiple search engines systematically without overwhelming complexity.
Solution Approach 2:
The system creates a universal framework that can handle multiple search engines through a single unified interface. The same infrastructure for query analysis, metadata matching, and result presentation works for all search engines, reducing overall system complexity while maintaining adaptability.
Data Source
AI summary
Methods and systems for incrementally selecting and providing relevant search engines in response to a user query. A method of incrementally selecting and providing relevant search engines is based in part on identifying a set of search engines associated with corresponding metadata, receiving a partial search query entered by the user of a device, inferring after each user keypress a set of potential full queries intended by the user, using the potential full queries and the search engine metadata to identify a set of relevant search engines, and for each of these search engines, providing a direct link to launch a relevant query in the search engine. The user input may be either ambiguous, or erroneous, and may be entered using an input-constrained device.