Rapid Document Tag Indexing via Text and Graph Segmentation
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Solution Overview
Problem
Conventional search engine crawlers face challenges in rapidly updating and indexing document tags due to their reliance on flat text analysis, which can lead to inefficiencies in managing relationships between tags and content documents, especially during outages or maintenance events.
Innovation Solution
A search service that receives a tag signal, stores the tag and its type, and indexes it as a tag document within a text-based index while managing relationships with content documents using a graph index, enabling rapid indexing and updating of document tags even during outages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional crawlers analyze documents as flat text files and build inverted indexes, then search queries can be retrieved, but updating and indexing document tags becomes very hard and slow
Solution Approach 1:
The patent segments the indexing system into two distinct components: a text-based index for storing tag documents and a graph index for managing relationships. This segmentation allows each index type to handle specific tasks efficiently, with the text-based index enabling rapid tag retrieval and the graph index managing complex tag-document relationships, thereby resolving the contradiction between tagging speed and management complexity.
Solution Approach 2:
The patent introduces a search service as an intermediary component that receives tag signals, processes them, and updates both the text-based index and graph index. This intermediary handles the complexity of coordinating updates across multiple index structures, shielding the tagging operation from complexity while maintaining high-speed tagging capability.
2Reliability
If conventional crawlers use flat text analysis, then documents can be indexed, but relationships between tags and content documents are hard to manage during outages or maintenance events
Solution Approach 1:
By separating relationship management into a dedicated graph index structure, the patent enables reliable tracking of tag-document relationships independent of the text-based index. The graph index specifically handles relationship data, allowing it to maintain integrity during outages or maintenance events affecting other system components, thus improving reliability without proportionally increasing overall complexity.
Solution Approach 2:
The search service acts as an intermediary that manages the complexity of maintaining relationships across both index types. It coordinates updates to the graph index when tags are added, removed, or modified, ensuring relationship integrity even during system outages or maintenance, thereby improving reliability while the intermediary absorbs the management complexity.
3Speed
If a text-based index is used for quick retrieval, then tag retrieval speed improves, but managing relationships between tags and documents becomes challenging
Solution Approach 1:
The patent divides the indexing system into a text-based index optimized for rapid tag retrieval and a graph index optimized for relationship management. The text-based index provides fast retrieval by storing tag documents in a format optimized for quick access, while the graph index separately handles the complexity of relationships, allowing each component to excel at its specific function without compromising the other.
Data Source
AI summary
Document tags are rapidly indexed using a text based index and a graph index. A tag signal is received. A tag and a type of the tag that are located in the tag signal are stored in a data store. The tag is indexed as a tag document in the text based index. One or more relationships between the tag and a content document are managed in the graph index.