Autosuggest Query Enrichment via Data Association
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Solution Overview
Problem
Users face challenges in determining the most relevant query suggestions in search systems due to insufficient information provided, making it difficult to select appropriate query results.
Innovation Solution
Enhanced query suggestions are generated by associating auto-suggested query terms with related data items such as text, images, videos, and hyperlinks, and using grammatical expansions based on user queries to provide additional context and information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If query suggestions are provided without additional data, then the system remains simple and fast, but users cannot make informed selections about which query to choose
Solution Approach 1:
The patent introduces an intermediary component that retrieves and associates additional data (such as knowledge graph entities, metadata, or contextual information) with query suggestions. This intermediary layer enriches the information provided to users without fundamentally redesigning the entire search system, thereby reducing information loss while controlling complexity growth through modular architecture.
Solution Approach 2:
The system segments the query suggestion functionality into distinct components: the base query suggestion engine, the data enrichment module, and the presentation layer. This segmentation allows each component to be optimized independently, enabling enhanced information provision without proportionally increasing overall system complexity.
2Measurement precision
If enhanced query suggestions with additional data items are provided, then user selection accuracy improves, but the time required to process and display suggestions increases
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching additional data items associated with potential query suggestions before they are actually needed. Knowledge graph entities and metadata are prepared in advance, so when a user types a query, the enrichment process is significantly accelerated, reducing the perceived processing time while maintaining high selection accuracy.
Solution Approach 2:
The system implements partial enrichment by selectively adding data items to only those query suggestions that benefit most from enhancement, rather than uniformly enriching all suggestions. This partial action approach provides sufficient information for accurate selection while avoiding the time overhead of processing excessive data for every suggestion.
3Adaptability or versatility
If multiple data items are associated with each query suggestion, then users have more information for decision-making, but the interface becomes more complex and harder to navigate
Solution Approach 1:
The interface applies local quality by presenting different types of data items in contextually appropriate locations and formats within the suggestion display. Each data item (such as knowledge graph entities, metadata, or contextual information) is positioned and styled according to its specific nature and relevance, making the enhanced information easy to scan and interpret without creating overall interface complexity.
Data Source
AI summary
Methods and computer-storage media having computer-executable instructions embodied thereon that facilitate determining enhanced query suggestions are provided. A plurality of query suggestions responsive to a user query are received. Items of data corresponding to the query suggestions are received. Based on the received query suggestions and the received items of data, enhanced query suggestions are determined. In embodiments, an enhanced query suggestion includes one or more items of data related to a respective query suggestion. A user may select at least a portion of an enhanced query suggestion. In embodiments, selection of a portion of an enhanced query suggestion provides additional information.