Query Reconstruction Server for Partial Search Input
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face difficulties in accessing the full depth of search engines on portable devices due to limitations in entering search queries, as they often require substantial effort and are not optimized for devices with decreased input capabilities.
Innovation Solution
A system and method for reconstructing a full search query from a partial query using a query reconstruction server, which compares the partial query to an index of known queries to determine matching and alternative queries, allowing for efficient submission to a search engine and presentation of results to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users enter full search queries manually on portable devices, then search accuracy is improved, but input effort and time consumption increase significantly
Solution Approach 1:
The system pre-processes and stores common search queries in an index database before user interaction. When a user inputs a partial query, the system quickly retrieves pre-prepared suggestions from the index, eliminating the need for users to type complete queries manually and reducing input time while maintaining search accuracy.
Solution Approach 2:
The query reconstruction server automatically analyzes the partial query input, compares it against the index of known queries, and generates suggested complete queries without requiring user intervention. The system serves itself by autonomously completing the query formulation process, freeing users from the burden of typing entire search queries.
2Ease of operation
If the system provides comprehensive query suggestions, then user convenience is improved, but system complexity increases
Solution Approach 1:
The query reconstruction system is divided into distinct functional modules: an indexing module that pre-processes queries, a comparison module that matches user input against the index, and a suggestion generation module that presents results. This segmentation allows each component to perform its specific function efficiently, managing overall system complexity through modular design.
Solution Approach 2:
The query index serves as an intermediary data structure between the user's partial query input and the search engine. Instead of directly complex processing, the system uses this pre-built index as a mediator to bridge the gap, simplifying the interaction while providing comprehensive suggestions.
3Measurement precision
If the system stores and compares against a comprehensive index of known queries, then query matching accuracy is improved, but memory requirements and processing overhead increase
Solution Approach 1:
The system extracts only the essential and most frequently used search queries to build the index, rather than storing all possible queries. By selecting and extracting the most relevant queries based on usage patterns and importance, the system achieves high matching accuracy with a more manageable index size, reducing memory requirements and processing overhead.
Data Source
AI summary
Methods and systems for reconstructing a full query based on a partial query are disclosed. Existing interfaces for search engines may be rigid and require users to submit full queries to perform searched. The methods and systems described herein may solve these problems by allowing a flexible way for users to submit a partial query and reconstruct a full query based on the partial query. A search may then be performed using the reconstructed query.