Recommendation Management Apparatus for User Behavior Impact Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing recommendation systems for smart devices lack effectiveness in recommending applications based on user behavior, as they primarily rely on frequency of use without considering the actual impact of introduced applications on user behavior over time.
Innovation Solution
A recommendation management apparatus and method that calculates difference information by analyzing user device history and action history before and after the introduction of an application, identifying changes in usage patterns to provide targeted recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If recommendation systems rely on frequency of use data, then they can provide basic application recommendations, but they lack effectiveness in accurately reflecting actual user behavior changes over time
Solution Approach 1:
The patent segments user behavior data into distinct time periods (before introduction and after introduction) and separates different data sources (use history from user device and action history from user actions). This segmentation allows for precise measurement of behavior changes by comparing specific time-bound datasets, directly addressing the need for accurate measurement of actual impact.
Solution Approach 2:
The patent collects and stores use history information and action history information before the introduction of new applications. By having preliminary data collected and organized in advance, the system can accurately measure the actual impact of introduced applications by comparing pre- and post-introduction behavior, preventing information loss about behavioral changes.
2Measurement precision
If the system collects detailed use history and action history data, then it can calculate accurate difference information, but the system complexity increases
Solution Approach 1:
The patent introduces a recommendation management apparatus as an intermediary component that专门 handles the collection, storage, and processing of use history and action history data. This intermediary system manages the complexity by providing a structured approach to data handling, with dedicated storage for different data types and organized processing workflows, making the complex data collection and processing manageable and systematic.
3Measurement precision
If the system analyzes behavior changes over time periods, then it can identify actual impact of applications, but the processing time increases
Solution Approach 1:
The patent performs preliminary organization and storage of use history and action history data in structured formats before analysis is needed. By having data pre-collected, pre-organized, and pre-stored in accessible formats, the system reduces the time required for actual analysis while maintaining measurement precision, as the data is ready for immediate comparison without extensive processing delays.
Data Source
AI summary
A recommendation management apparatus includes circuitry. The circuitry manages a user device associated with customer identification information for identifying a customer, a user associated with the customer identification information, and introduction object identification information for identifying an introduction object introduced in association with the customer identification information. The circuitry acquires use history information relating to a use history of the user device. The circuitry acquires action history information relating to an action history of the user. The circuitry calculates difference information indicating a difference between pre-introduction history information for a predetermined period before introduction of the introduction object indicated in the introduction object identification information and post-introduction history information for a predetermined period after the introduction of the introduction object indicated in the introduction object identification information, based on the use history information and the action history information.