Document Discovery Notifications for Relevant Cloud File Retrieval
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Solution Overview
Problem
The continued growth in the number of documents accessible via cloud-based content management platforms makes locating and retrieving relevant documents more resource-intensive, consuming network and processing resources, and users may not be aware of or remember documents that have changed since their last access.
Innovation Solution
A system and method for predicting and notifying users about documents of interest using a graphical user interface (GUI) that includes suggestion cards, which are generated based on document overlap, user interactions, and collaborative events, allowing quick access without explicit user action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users manually locate and retrieve documents from cloud storage, then users can access documents they are aware of, but the process consumes network and processing resources and users may not discover changed documents they don't remember
Solution Approach 1:
The system performs preliminary analysis of document changes, user patterns, and document relationships before the user needs to retrieve documents. It pre-identifies potentially relevant documents and prepares recommendation data, so that when the user accesses cloud storage, the system can quickly present relevant documents without requiring extensive real-time resource consumption for analysis.
Solution Approach 2:
The system enables documents to 'self-recommend' themselves by automatically analyzing their own change status, metadata, and relationships with other documents. The system serves itself by autonomously identifying which documents should be presented to users based on objective criteria such as modification status, collaboration activity, and topical relevance, eliminating the need for users to manually search through all documents.
2Ease of operation
If the system presents all documents to users, then users have complete access to all available documents, but the interface becomes overwhelming and users cannot efficiently locate relevant documents
Solution Approach 1:
The system applies different presentation qualities to different documents based on their relevance to the user. Rather than presenting all documents uniformly, it enhances the visibility and prominence of highly relevant documents (such as recently modified documents, collaboratively edited documents, or documents matching user patterns) while presenting less relevant documents in a more subdued manner. This creates a differentiated interface where important documents stand out naturally.
Solution Approach 2:
The system segments the document collection into multiple categories or groups based on relevance criteria such as recent modifications, collaboration activity, topical similarity, and user access patterns. Instead of presenting a single flat list of all documents, it organizes documents into segmented groups (such as 'Recently Modified,' 'Collaborative Documents,' 'Related Documents') allowing users to efficiently navigate to relevant sections without being overwhelmed by the complete document set.
3Measurement precision
If the system analyzes user interactions and document characteristics to select comments for notification, then notification accuracy improves, but processing requirements increase
Solution Approach 1:
The system dynamically adjusts analysis parameters such as the time window for considering user interactions, the weight given to different interaction types (views, edits, comments), and the threshold for notification eligibility. By changing these parameters based on user context, document type, and system load, the system can optimize the balance between notification accuracy and processing requirements, intensifying analysis when high precision is needed and reducing it when efficiency is prioritized.
Data Source
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AI summary
A method of notifying a document to a user of a cloud-based content management platform including identifying a first set of documents, wherein the first set of documents is hosted by the cloud-based content management platform and does not include one or more documents recently opened by the user, identifying one or more target documents from the first set of documents for the user based on an amount of overlap in topicality between a respective document and a users current working set of documents, a number of view events of the respective document, and a number of collaborative events associated with the respective document, wherein the users current working set of documents comprises documents the user has accessed within a last predetermined time period via the cloud-based content management platform, providing a graphical user interface (GUI) of a cloud storage of the user hosted by the cloud-based content management platform for presentation to the user, the GUI identifying the one or more target documents.