Context-Aware Search Query Enhancement via IoT Correlation
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Solution Overview
Problem
Current search engines often provide search results that are not contextually relevant to the user's immediate environment or interests, as they do not effectively incorporate data from nearby IoT devices or user profiles, leading to less accurate and less relevant search results.
Innovation Solution
A system that receives search results from a search engine, collects data from proximate IoT devices, determines correlation parameters between search results and device content, and user interests, and generates a new search query with improved terms based on these correlations to enhance relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If search engines use traditional search queries without context analysis, then the search process is simple and fast, but the search results lack contextual relevance to user environment and interests
Solution Approach 1:
The system performs preliminary actions by collecting data from IoT devices and analyzing user profiles before executing the search query. This pre-processing of contextual information enables more relevant search results without adding complexity to the core search engine operations.
Solution Approach 2:
The system introduces an intermediary contextual analysis layer between the user's search query and the search engine. This intermediary component processes IoT device data and user profile information to generate enhanced search queries, thereby improving relevance without directly modifying the search engine itself.
2Measurement precision
If search engines incorporate data from multiple IoT devices and user profiles, then search result accuracy improves, but the time required to process and analyze the data increases
Solution Approach 1:
The system collects and pre-processes data from IoT devices and user profiles before the search query is executed. By having this contextual data ready in advance, the system minimizes additional processing time during the actual search operation while maintaining high accuracy.
Solution Approach 2:
The system selectively processes only the most relevant IoT device data and user profile information needed for the specific search context, rather than analyzing all available data. This partial processing approach reduces time consumption while still achieving accurate search results.
Data Source
AI summary
The context in which a user generates a search query is analyzed to generate an improved search query. Search query context may be determined with reference to a user profile or content collected from Internet of Things (IoT) or non-IoT devices located proximate the user. Content may be collected when the search query is generated or at a time before the search query is generated. Content collected for context analysis includes visual display content (screen capture), audio content, and data content.