Dynamic Query Tag System for User Attribute Detection
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Solution Overview
Problem
Existing methods fail to intelligently identify potential users outside the originally intended user segment for a given query and do not adequately capture the context of a user's decision to engage or respond to the query.
Innovation Solution
A method and system that involves sending a query with query tags corresponding to expected user attributes, detecting user attributes, incrementing numerical values associated with matching query tags based on user responses, creating new query tags for undetected attributes, and storing these values to refine user identification and query targeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing methods are used to identify users for queries, then the originally intended user segment is identified, but potential users outside this segment are not identified
Solution Approach 1:
The system implements feedback loops where user responses to queries are continuously analyzed to update and refine user attributes. This feedback mechanism enables the system to learn from actual user behavior and expand user identification beyond initial segments, thereby improving adaptability while capturing decision context through attribute updates.
Solution Approach 2:
The system performs preliminary detection of user attributes before querying, and then uses the results to dynamically expand the target user segment. By preparing and detecting attributes in advance and using them to identify additional potential users, the system overcomes the limitation of static user segmentation.
2Productivity
If query tags are created only for known user attributes, then the query targeting is simple, but additional potential users outside the intended segment cannot be identified
Solution Approach 1:
The query tag system is made dynamic by automatically creating new query tags based on detected user attributes that were not previously anticipated. This dynamic adaptation allows the system to maintain efficient querying while expanding coverage to include previously unidentified potential users, resolving the contradiction between efficiency and versatility.
Solution Approach 2:
The query tag database serves multiple functions: it stores predefined attributes for efficient targeting, dynamically accepts new attributes from user detection, and uses numerical values to prioritize multiple attributes simultaneously. This multi-functionality enables both efficient processing and expanded user identification.
3Measurement precision
If numerical values are incremented for all detected attributes, then comprehensive user profiling is achieved, but the system complexity increases
Solution Approach 1:
The system uses numerical values as parameters to represent the importance or match quality of each query tag. By incrementing these numerical values based on user responses, the system achieves precise user profiling through a simple quantitative mechanism rather than complex structural changes, maintaining database simplicity while improving measurement precision.
Data Source
AI summary
A method and system of improving the detection and utilization of attributes of a user. A query is sent to a device operated by a user. The query includes a query database having a plurality of query tags corresponding to expected attributes of a target user and a numerical value associated with each of the plurality of query tags. A plurality of attributes of the user of the device is detected. Data corresponding to the detected plurality of attributes of the user and a response from the user related to the query is received. The numerical value associated with each of the plurality of query tags that corresponds with each of the detected plurality of attributes and creating a new query tags is incremented.