Analysis of Dynamic Memory Management Mechanisms
Memobase's time-aware feature uses a two-tier architecture for intelligent memory management:
- Time Stamp Marking System: Each stored data unit records a creation/update timestamp, e.g. storing a user saying 'I like to swim' will also record the date stamp 2024-03-15
- Timeliness weighting algorithm: The system has a built-in decay function, so that the older the information, the lower the weight in the AI decision (configurable decay curves).
- Active phase-out mechanisms: Developers can set thresholds to automatically archive or delete outdated data, e.g., ignoring campaign preferences from 2 years ago
Technically implemented, the feature is controlled via the following API parameters:
valid_daysSetting the message expiration datepriority_scoreDefining time sensitivity- Supporting the use of
filter_by_date()Methods for historical data query
This design avoids 'users said they hated coffee three years ago' affecting the accuracy of recommendations now, while preserving key long-term features (e.g., native language information).
This answer comes from the articleMemobase: a user profile-based long-term memory solution for AI applicationsThe
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