Information Processing Apparatus for Personalized Anomaly Notification
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Solution Overview
Problem
Existing systems struggle to provide meaningful notifications based on unusual user behavior detection, as they rely on uniform criteria that do not account for individual user differences.
Innovation Solution
An information processing apparatus and method that compares detected time series data with pre-stored data to detect unusualness and controls notification timing based on the content of the detected unusualness, using a processing unit and notification unit to provide personalized notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a uniform criterion is applied to all users to determine unusualness, then the system is simple and easy to implement, but the detection accuracy and meaningfulness of notifications deteriorate because individual user differences are not accounted for
Solution Approach 1:
The patent segments the user base into individual user profiles, each with their own baseline behavior patterns. Instead of applying a single uniform criterion to all users, the system divides the detection process into user-specific segments that can be independently analyzed and compared against personalized historical data.
Solution Approach 2:
The patent implements local quality by creating user-specific determination criteria rather than applying a uniform standard globally. Each user develops their own baseline behavior pattern through accumulated historical data, allowing the detection sensitivity and thresholds to be locally optimized for each individual's unique behavior characteristics.
2Measurement precision
If user-specific determination criteria are created through accumulated behavior data, then detection accuracy and notification meaningfulness improve, but the system complexity and data storage requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and accumulating user behavior data over time to establish baseline patterns before actual unusualness detection occurs. The system proactively builds user profiles and determination criteria in advance, so that when detection is needed, the complex analytical work has already been completed during the data accumulation phase.
Solution Approach 2:
The patent uses copying by creating simplified representations of user behavior patterns (templates or profiles) that capture essential characteristics without storing all raw data. These copied behavioral models can be efficiently stored and compared, reducing the complexity of handling full historical datasets while maintaining detection accuracy.
3Loss of information
If notification timing is controlled based on the content of detected unusualness, then the meaningfulness and appropriateness of notifications improve, but the processing complexity and computational resources required increase
Solution Approach 1:
The patent implements dynamics by making notification timing adaptive rather than static. The notification timing is dynamically adjusted based on the specific content and characteristics of the detected unusualness, allowing the system to respond flexibly to different types of anomalies with appropriately timed notifications that maximize user awareness and response.
Solution Approach 2:
The patent applies parameter changes by modifying notification timing parameters based on the content of detected unusualness. Different unusualness patterns trigger different timing parameters, such as immediate notifications for critical anomalies versus delayed or contextualized notifications for less urgent patterns, optimizing the balance between timely alerting and avoiding notification fatigue.
Data Source
AI summary
To provide an information processing apparatus including a processing unit that compares detected time series data and time series data stored in advance to detect unusualness, and a notification unit that controls, when the unusualness is detected by the processing unit, a timing of notification in accordance with a content of the detected unusualness.