Search Intent Prediction via Contextual Analysis
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Solution Overview
Problem
Users face stress and resource wastage due to the need to sift through excessive search results when searching for specific information, as current computing devices often return irrelevant information alongside relevant data.
Innovation Solution
A computing system predicts the intent behind a search query based on contextual information, adjusting search results to emphasize information that satisfies the user's intent, thereby reducing the time and effort required to find relevant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a computing device returns comprehensive search results for a search query, then the quantity of information provided is improved, but the user experiences stress and wastes time sifting through excessive results
Solution Approach 1:
The system performs preliminary actions by analyzing contextual information (location, time, device state, recent activities) before generating search results. This allows the system to pre-determine which results are most relevant to the user's current situation, effectively filtering and prioritizing information before presentation. The context analysis and intent prediction occur in advance of result delivery, reducing the user's need to manually sift through irrelevant results.
2Measurement precision
If a computing device requires detailed queries from users to obtain specific information, then the precision of information retrieval is improved, but the ease of operation deteriorates due to user stress and resource input
Solution Approach 1:
The system applies self-service by automatically analyzing contextual information and predicting user intent without requiring explicit detailed queries. The computing device serves itself by interpreting the user's simple search term within the context of their current situation (location, time, recent activities, device state), thereby autonomously determining the most relevant results. This eliminates the need for users to manually craft detailed queries while maintaining high retrieval precision.
3Reliability
If a computing system executes multiple searches to locate specific information, then the reliability of finding relevant information is improved, but the productivity deteriorates due to multiple search executions
Solution Approach 1:
The system performs preliminary context analysis and intent prediction before executing searches, allowing it to formulate more precise search strategies from the outset. By understanding the user's situation and likely information needs in advance, the system can execute fewer, more targeted searches that are more likely to yield relevant results on the first attempt, thereby improving productivity while maintaining reliability.
Data Source
AI summary
A computing system is described that determines, based on user-initiated actions performed by a group of computing devices, an intent of a search using a particular search query received from a computing device. The computing system adjusts, based on the intent, at least a particular portion of search results obtained from the search using the search query by emphasizing information that satisfies the intent. The computing system sends, to the computing device, an indication of the adjusted search results.