Cold-Start User Profile Generation via Interactive Questioning
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Solution Overview
Problem
Existing online community question-answering networks face challenges in presenting relevant questions to new users without historical interaction data, as they are reluctant to fill formal questionnaires, and existing methods are not applicable to new users, leading to a lack of user profile generation for personalized experiences.
Innovation Solution
A cold-start method involving an interactive interface that presents users with representative questions, allowing them to indicate preferences, which are used to generate a user profile through iterative responses, eliminating the need for historical data and creating a playful game-like experience to engage new users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If formal questionnaires are used to collect user preferences, then user profile accuracy is improved, but user participation decreases
Solution Approach 1:
The system automatically infers user preferences from historical interaction data without requiring users to manually complete questionnaires. The learning module continuously analyzes user behavior patterns and updates profiles in the background, allowing the system to serve itself by extracting preference information from existing interaction logs rather than burdening users with explicit preference collection.
Solution Approach 2:
The system uses iterative feedback loops where user interactions with recommended questions and content continuously refine the user profile. The learning module processes feedback from user behavior (clicks, time spent, questions asked) and adjusts preference models accordingly, improving accuracy over time without requiring explicit user input.
2Measurement precision
If historical interaction data is used to infer user preferences, then personalized recommendations are improved, but applicability to new users deteriorates
Solution Approach 1:
The system performs preliminary preference collection through an interactive questioning module that presents curated questions to new users upon registration. This preliminary action gathers initial preference data before the user has generated sufficient historical interaction data, enabling the system to create initial user profiles and provide personalized recommendations from the very first interaction.
Solution Approach 2:
The preference collection process is segmented into multiple phases: initial questionnaire-based preference gathering for new users, followed by continuous refinement through interaction analysis. This segmentation allows the system to handle new users differently from established users, applying appropriate methods for each user state and ensuring smooth transition as users accumulate interaction history.
3Productivity
If new users are retained without personalized recommendations, then traffic opportunity is preserved, but user engagement deteriorates
Solution Approach 1:
The system implements preliminary preference collection and profile generation during the user registration and initial browsing phase. By proactively gathering preference information through the questioning module before users leave, the system prepares personalized recommendation capabilities in advance, ensuring that personalized content is ready when users return, thus maintaining both retention and engagement.
Solution Approach 2:
The system accelerates the preference learning process for new users by using intensive questioning modules and rapid profile generation during initial interactions. This rushing through the cold-start phase allows the system to quickly establish personalized recommendation capabilities, preventing user dropout during the critical early period while maintaining engagement quality.
Data Source
AI summary
A system and method for learning a new user's interests in the absence of historical data includes: generating a user interface on which a user interacts in a session; formulating questions such that a user response to the questions indicates a preference; presenting the questions to the user on the user interface; receiving responses from the user, the responses indicating user preferences; and populating a new user profile with the user preferences. The steps of presenting, receiving, and populating are repeated until the session terminates.