Enterprise Search Indexing with Contextual Boundaries
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing enterprise search systems fail to provide relevant search results by not considering the contextual boundaries and user roles within the enterprise, leading to inefficient retrieval and presentation of information.
Innovation Solution
A search indexer extracts document structures and layouts to create a platform-independent search index, which includes contextual boundaries and user role data, allowing the search processor to filter and arrange results based on user roles and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a search engine searches electronic documents using traditional methods, then search results are generated, but the results lack contextual accuracy and role-specific relevance
Solution Approach 1:
The search indexer performs preliminary actions by extracting document structures, identifying contextual boundaries, and creating platform-independent indexes before search queries are executed. This pre-processing enables the search processor to quickly retrieve and filter results based on user roles without performing complex analysis during the actual search operation.
Solution Approach 2:
The patent introduces an intermediary search index that acts as a mediator between the document storage system and the search processor. This index contains pre-extracted structural information and contextual boundaries, allowing the search processor to efficiently filter and rank results based on user roles without directly accessing the original documents.
2Measurement precision
If the search system extracts and stores contextual boundaries for all documents, then search result accuracy improves, but the time and resources required for indexing increase
Solution Approach 1:
The patent segments the document processing into distinct components: document structure extraction, contextual boundary identification, and index creation. This segmentation allows each component to be optimized independently and enables parallel processing, reducing the overall indexing time while maintaining accuracy.
Solution Approach 2:
The search indexer creates a platform-independent copy of the document structure that contains essential contextual information without replicating the entire document. This copied structural representation is sufficient for search operations, significantly reducing indexing time compared to processing full documents while maintaining contextual accuracy.
3Productivity
If the search processor filters results based on user roles and preferences, then information retrieval quality improves, but the processing complexity increases
Solution Approach 1:
User role data and preferences are retrieved and prepared in advance before the search results are filtered. This preliminary preparation of user context information allows the search processor to efficiently apply filtering rules without complex real-time analysis, improving retrieval efficiency while managing processing complexity.
Data Source
AI summary
A server device obtains a search term from a client device that is managed by an enterprise. A user associated with the client device is identified. Search index data that specifies a location for a term and a contextual boundary for the term is obtained. A search result that is based on the search index data and the role of the user for the enterprise is generated.