Query Formation with Visual Indicators for Missing Terms
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional data retrieval methods on data-driven websites are inefficient and time-consuming, often resulting in frustration for users due to complex navigation and irrelevant search results.
Innovation Solution
A query formation and modification technique that assists users in forming queries as phrases in human-readable language, using visual indicators to represent missing terms, with auto-completion options and database searches to provide targeted results directly in the query field.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data retrieval methods are used, then users can access data, but the process is time-consuming and frustrating due to complex navigation interfaces
Solution Approach 1:
The system automatically generates and modifies search queries based on the current interface state and user selections, eliminating the need for users to manually construct complex search syntax. The query generation occurs self-service through automated analysis of the interface and user interactions.
Solution Approach 2:
The system pre-generates multiple possible search queries before the user completes their data retrieval task. By anticipating what queries the user might need based on the current interface state and selections made, the system prepares query options in advance, reducing the time users would otherwise spend formulating searches.
2Measurement precision
If users provide queries in traditional search interfaces, then data can be retrieved, but the results are often random and unrelated to the actual query intent
Solution Approach 1:
The system continuously monitors user selections and interface state changes, using this feedback to dynamically refine and modify search queries. As users interact with the interface and make selections, the query is updated in real-time to better align with their actual intent, ensuring relevant results.
Solution Approach 2:
The search query is not a static input but a dynamic construct that automatically adapts based on the current interface state and user interactions. The query morphology changes dynamically as users make selections, transforming from a generic search into a targeted query that reflects their specific needs.
3Adaptability or versatility
If complex query interfaces are provided, then data can be searched, but the interface complexity increases navigation difficulty and user frustration
Solution Approach 1:
The system introduces an intermediary layer between the simple user interface and the complex search functionality. This intermediary automatically translates simple user selections and interface state into appropriate search queries, shielding users from the complexity of the underlying search system while maintaining full search capability.
Solution Approach 2:
The search functionality is segmented into multiple automated query generation passes, with each pass handling a specific aspect of the search. Rather than requiring users to construct a single complex query, the system divides the query formation process into manageable segments that are handled automatically at different stages.
Data Source
AI summary
Query formation and modification techniques are described. In one or more embodiments, a query is received that is formed in a text field as a phrase in a human-readable language that includes a visual indicator that represents a missing term that is a subject of the query. Based on the query, a defined database is searched, and one or more modified versions of the phrase are presented that replace the visual indicator with a respective result of the searching. In addition, one or more options are presented that are selectable to automatically complete the phrase as a sentence in the human-readable language.