Context-Aware Query Disambiguation Using Item Ensemble Detection
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Solution Overview
Problem
Modern computer systems struggle to disambiguate user search queries due to lack of consideration for the user's physical environment, often delivering inappropriate results that require refinement or abandonment of the search.
Innovation Solution
A media guidance application uses sensors to identify ensembles of items in the user's vicinity, associating them with predefined templates to disambiguate search queries by adding relevant keywords, thereby refining the search based on the user's context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional disambiguation techniques using user profile data are used, then the system can provide search results, but the results are often inappropriate for the user's current physical environment
Solution Approach 1:
The patent introduces a new dimension of analysis by detecting the physical arrangement of items in the user's environment (spatial configuration) and using this dimensional information to disambiguate search queries. Instead of relying solely on temporal or profile-based data, the system now incorporates spatial context from sensor data to determine item ensembles and their arrangements, thereby improving search relevance adaptation to physical environments.
2Productivity
If the system does not account for physical environment state, then the system remains simple, but search performance deteriorates
Solution Approach 1:
The patent introduces sensor data as an intermediary element that bridges the user's physical environment and the search system. Sensors detect item arrangements and provide this environmental context as intermediate information to the disambiguation process, enabling improved search performance without requiring the system to directly interpret complex physical scenarios.
Solution Approach 2:
The patent replaces traditional mechanical or manual disambiguation approaches with automated sensor-based detection. Instead of relying on users to manually provide context or using simple profile data, the system uses sensor arrays to automatically detect and interpret physical item arrangements, substituting a more sophisticated automated system for simpler but less effective methods.
3Measurement precision
If multiple sensors are used to detect item ensembles, then the precision of environmental detection improves, but the device complexity increases
Solution Approach 1:
The patent segments the detection task by using multiple specialized sensors, each detecting different aspects of the physical environment (e.g., object detection, spatial positioning, recognition). This segmentation allows the system to achieve high measurement precision for item ensemble detection while managing complexity through modular sensor integration and specialized functionality.
Data Source
AI summary
Systems and methods are described for disambiguating user input based on a physical location of items in a vicinity of a user. The system determines that a query received from a user contains an ambiguity. In response, the system identifies several items in the physical vicinity of the user. Then, the system analyzes the identified plurality of items to determine whether the plurality of items forms a first ensemble of items or a second ensemble of items. If the plurality of items forms a first ensemble of items, the system performs a search using the search query and a first keyword related to the first ensemble of items. If the plurality of items forms a second ensemble of items, the system performs a search using the search query and a second keyword related to the second ensemble of items. The system then outputs results of the performed search.