Real-time Query Expansion Interface for Handheld Devices
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Solution Overview
Problem
Existing real-time query expansion (RTQE) interfaces on handheld devices are inefficient due to limited memory space and usability issues, requiring users to manually type entire phrases, which is cumbersome and reduces search accuracy.
Innovation Solution
A method that presents users with lists of terms, where the content of subsequent lists is dynamically updated based on user input and term focus, allowing for flexible phrase construction by selecting associated terms, reducing keystrokes and enhancing search accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually type entire phrases on handheld devices, then text entry completeness is ensured, but usability and efficiency deteriorate due to cumbersome keystrokes
Solution Approach 1:
The system pre-loads and stores frequently used terms and phrase components in a database on the handheld device. When a user begins typing, the system proactively retrieves and displays relevant pre-stored terms and expansions, allowing users to complete phrases by selecting from presented options rather than typing everything manually.
Solution Approach 2:
As users type each character, the system provides real-time feedback by dynamically updating the display to show matching terms from the database, suggested completions, and related expansions. This feedback loop continues with each keystroke, guiding users toward complete phrase construction with minimal input.
2Measurement precision
If comprehensive term databases are stored on handheld devices for real-time query expansion, then search accuracy improves, but memory space requirements increase
Solution Approach 1:
Instead of storing a single uniform comprehensive database, the system organizes term data into multiple specialized databases categorized by topic, frequency, and relevance. Each database contains terms optimized for specific contexts, allowing the system to load only the most relevant term sets for current search conditions, reducing overall memory requirements while maintaining high search accuracy.
Solution Approach 2:
The term database is segmented into hierarchical levels: frequently used terms stored in high-speed memory, less frequent terms in secondary storage, and expansion rules distributed across multiple category files. This segmentation allows selective loading of database portions based on user input patterns, balancing memory usage with comprehensive search capability.
3Adaptability or versatility
If all terms are displayed in lists for user selection, then completeness of options is ensured, but display compactness and usability deteriorate
Solution Approach 1:
The term display lists are dynamically adjusted based on user input progress. As users type characters, the system filters and reorders displayed terms in real-time, highlighting matches and repositioning relevant options. The display automatically expands or contracts to show only the most relevant subset of terms at each stage, maintaining flexibility while optimizing display space utilization.
Data Source
AI summary
Real-time query expansion (RTQE) is a process of supplementing an original query with additional terms or expansion choices that are ranked according to some figure of merit and presented while users are still formulating their queries. As disclosed herein, individual terms may be combined and submitted as a phrase into a query. By building the phase term-by-term, users can compositionally formulate queries while maintaining the same benefits that other RTQE interfaces offer. To promote greater flexibility in its working environment, the number of terms that are presented on a display may be reduced. In place of some terms, placeholders may be used and expanded by the user when necessary. This allows phrases to be readily presented on small displays (e.g., hand-held devices).