Enterprise Graph Content Aggregation for Distributed Storage
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Solution Overview
Problem
In enterprises, content items are scattered across various workloads and storage systems, making it difficult for users to find relevant content, often requiring time-consuming searches or duplication of effort, as users may not be aware of existing relevant content.
Innovation Solution
An enterprise graph connects individuals and content by tracking user activities, recommending relevant content based on personalized implicit and explicit activity signals, and allows users to aggregate content around user-generated topics, providing a centralized view of content through a landing page with relevance ranking and topic-based navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is stored across multiple workloads and storage systems, then content storage capacity and organization flexibility are improved, but content search time and user effort increase
Solution Approach 1:
The patent introduces an enterprise graph as an intermediary layer that indexes and connects content items across multiple workloads and storage systems. This graph structure enables users to search for content without needing to navigate through the underlying distributed storage architecture, effectively mediating between the flexible multi-system storage and efficient content retrieval.
Solution Approach 2:
The system implements feedback mechanisms by tracking user activities (viewing, sharing, modifying content) and using this information to improve content recommendations and search results. This feedback loop allows the system to learn from user interactions and progressively improve content discoverability, reducing search time over time.
2Loss of information
If users manually search for content across different systems, then content discovery completeness may improve, but user effort and time consumption increase
Solution Approach 1:
The enterprise graph performs preliminary indexing and organization of all content items across the enterprise before users need to search. By pre-processing and structuring the content relationships in advance, the system eliminates the need for users to manually navigate through multiple systems, providing both complete content discovery and ease of operation simultaneously.
Solution Approach 2:
The system provides self-service content discovery by automatically recommending relevant content based on user activities and enterprise graph relationships. Instead of requiring users to actively search for content, the system proactively presents relevant content items, reducing user effort while maintaining discovery completeness.
3Device complexity
If content is distributed across individual workloads, then workload independence and system modularity are improved, but content aggregation and user awareness decrease
Solution Approach 1:
The patent adds a new dimensional layer (the enterprise graph) that sits above the distributed workload architecture. This additional dimension enables content aggregation and cross-workload relationships without changing or complicating the underlying modular workload structure, allowing both workload independence and improved user awareness to coexist.
Data Source
AI summary
Aggregation of content based on user-generated topics is provided. Users may associate one or more topics with content items stored across various workloads and repositories. A topic may be a word or phrase of the user's choice, and may be utilized for discoverability of information and aggregation of content items. Topics and content items associated with topics may be acted on (e.g., a user may add or delete topics to associate with a content item, associate or disassociate content items with a topic, embed a set of content items or a stream of content items associated with a topic into other experiences, follow topics, etc.). Content items identified as related to a specific topic may be automatically suggested as possible content items of interest to the user. Additionally, when a user follows a topic, the user may be notified of any changes that occur to the topic.