Privacy-Aware Historical Search Suggestions Using Environmental Signals
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Solution Overview
Problem
Users desire privacy in search query submissions while interacting with search interfaces, but existing private browsing modes restrict historical query suggestions, requiring excessive user input to resubmit queries.
Innovation Solution
Generate privacy measures based on environmental signals and user input to adapt presentation of historical search queries, ensuring only relevant queries are suggested based on the current environment and privacy level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If private browsing mode is used to ensure privacy, then user privacy is protected, but historical search queries cannot be presented as suggestions and users must re-submit queries manually
Solution Approach 1:
The system dynamically adjusts the presentation of historical search queries based on the detected privacy level of the current environment. When a high privacy level is detected, private queries are excluded from suggestions. When a low privacy level is detected, both private and public queries can be suggested. This dynamic adaptation resolves the contradiction by making the system behavior flexible rather than fixed, allowing it to provide suggestions when appropriate while protecting privacy when needed.
Solution Approach 2:
The system changes the parameter of query suggestion visibility based on the privacy level parameter derived from environmental signals. By mapping environmental characteristics (presence of others, location type) to a privacy level parameter, the system controls which historical queries are presented. This parameter-based control allows the system to maintain privacy protection while enabling convenient query suggestions when the environment is safe.
2Ease of operation
If all historical search queries are presented as suggestions, then user convenience is improved, but user privacy may be compromised in public environments
Solution Approach 1:
The system uses environmental signals (audio, vision, location data) as feedback to determine the privacy level and adjust query suggestion behavior accordingly. The feedback loop continuously monitors the environment and modifies the set of suggested queries in real-time. This ensures that privacy-sensitive queries are not suggested when others are nearby, while still providing convenient suggestions when the user is alone.
Solution Approach 2:
The system applies different quality levels to different historical queries based on their privacy characteristics and the current environment. Instead of uniformly showing or hiding all suggestions, it selectively presents queries based on their sensitivity and the detected privacy level. This local differentiation allows the system to maximize convenience for public queries while protecting private queries in appropriate contexts.
3Reliability
If privacy measures are strictly enforced by blocking all historical queries, then privacy is protected, but computational and network resources are wasted by requiring users to re-submit queries
Solution Approach 1:
Instead of completely blocking all historical query suggestions (excessive action), the system applies partial action by selectively suggesting only those queries appropriate for the current privacy level. This partial suggestion approach protects privacy for sensitive queries while still providing useful suggestions for non-sensitive queries, thereby reducing the need for users to re-submit queries and conserving computational and network resources.
Data Source
AI summary
Implementations are directed to receiving a search query from a user, obtaining environmental signal(s) associated with an environment in which the user is located when the search query is received, processing the environmental signal(s) to generate a privacy measure associated with submission of the search query, obtaining additional environmental signal(s) associated with the environment in which the user is located when user input directed to a search interface is received, processing the additional environmental signal(s) to generate an additional privacy measure associated with the user input, selecting, from a superset of historical search queries of the user, a subset of the historical search queries based on at least the privacy measure and the additional privacy measure, and causing the subset of the historical search queries to be presented to the user in response to receiving the user input directed to the search interface.