Activity Assistant System for Personalized Context-Aware Recommendations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies lack an effective solution for providing users with personalized and dynamically tailored activities based on their interests, mood, location, and intent, leading to inefficient activity selection and management.
Innovation Solution
An activity assistant system that uses user-defined parameters, such as mood, location, and desired participation, to score and rank activities, offering a customizable and intuitive user interface for activity selection and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If activities are presented in a fixed, non-personalized manner, then the system is simple to implement, but user engagement and relevance are reduced
Solution Approach 1:
The system changes parameters such as activity ordering, filtering, and presentation based on user profile attributes (age, location, interests) and contextual factors (time of day, weather). This allows the same system to adapt its behavior to different users and situations without requiring fundamentally different system architectures.
Solution Approach 2:
The activity presentation dynamically adjusts based on real-time user context and profile data. The system continuously updates activity lists, recommendations, and displays according to changing user preferences, locations, and circumstances, transforming a static system into a dynamic one that responds to user needs.
2Measurement precision
If multiple user parameters are collected and processed, then activity relevance improves, but data processing requirements increase
Solution Approach 1:
The system segments user context into distinct parameters (location, time, interests, mood) and processes each independently through specialized modules. This segmentation allows efficient handling of multiple parameters without requiring the entire system to process all data simultaneously, reducing overall processing power requirements.
Solution Approach 2:
User profiles and preferences are pre-processed and stored before actual activity selection. Historical data is analyzed in advance to establish baseline preferences, allowing the system to quickly retrieve and apply relevant information during real-time activity recommendations without intensive processing at the moment of decision.
3Ease of operation
If activities are manually selected from comprehensive lists, then user control is maintained, but time consumption increases
Solution Approach 1:
The system performs preliminary sorting, filtering, and ranking of activities based on user profiles and context before presentation. Activities are pre-organized into prioritized lists with relevant information highlighted, so users receive ready-to-review recommendations rather than raw data requiring manual analysis from scratch.
Solution Approach 2:
The system incorporates feedback loops where user interactions with presented activities (selections, skips, likes) are recorded and used to refine future recommendations. This feedback mechanism continuously improves accuracy, reducing the need for users to manually search through irrelevant options and decreasing decision time over time.
Data Source
AI summary
Disclosed herein is an “activity assistant” and an “activity assistant user interface” that provides users with dynamically-selected “activities” that are intelligently tailored to the user's world. For example, a graphical UI includes selectable context elements, each of which corresponds to a user-attribute whose value provides a signal to the activity assistant. In response to selecting a parameter associated with at least one of the selectable context elements, a first signal is generated and provided to the activity assistant. In response to providing the signal, one or more activities are populated and ordered based, at least in part, on the signal, and subsequently displayed. The parameters may include a current mood of a user, a current location of the user, associations with other users, and a time during which the user desires to carry out the activity in some examples.