Context-Aware Search Indexing for Enterprise Portals
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Solution Overview
Problem
Companies face challenges in efficiently locating and accessing information across multiple portals and websites, leading to a significant workload for human resources personnel due to irrelevant search results and lack of user context consideration in existing search tools.
Innovation Solution
A computer-implemented method and system that indexes organization information from various portals and websites based on structural attributes and company-relevant parameters, using a natural language interface to interpret user queries within a specific data context, and re-indexes results based on user feedback to provide relevant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If standard search tools are used to search company portals, then search coverage is improved, but search result relevance deteriorates
Solution Approach 1:
The system dynamically changes indexing parameters and search weights based on user context, feedback, and interaction patterns. This allows the search system to adapt the relevance criteria beyond static keyword matching, improving result precision while maintaining broad coverage across multiple company portals.
Solution Approach 2:
The system incorporates user feedback loops where search results are continuously evaluated and used to refine future search indexing and ranking. This feedback mechanism enables the system to learn from user interactions and improve relevance over time without sacrificing the comprehensive search coverage across organizational portals.
2Loss of information
If comprehensive search across multiple portals is implemented, then information availability is improved, but system complexity deteriorates
Solution Approach 1:
The system segments the search index into modular components corresponding to different company portals and data sources. Each portal maintains its own indexed structure while the system provides a unified search interface, reducing overall complexity by allowing independent management of each data source while achieving comprehensive information availability.
Solution Approach 2:
The patent introduces an intermediary indexing layer that sits between multiple company portals and the user interface. This intermediary layer handles the complexity of data aggregation, normalization, and cross-portal searching, making the system manageable by isolating complexity in a dedicated component rather than distributing it across all portals.
3Measurement precision
If user context is considered in search, then search accuracy is improved, but processing time deteriorates
Solution Approach 1:
The system performs preliminary indexing of user context, preferences, and interaction patterns during off-peak times or in advance of actual search operations. By pre-processing and storing contextual information in optimized data structures, the system can quickly retrieve and apply user context during searches without adding significant processing time to the search operation itself.
4Measurement precision
If interactive re-indexing is performed based on feedback, then search relevance is improved, but computational overhead deteriorates
Solution Approach 1:
Instead of performing full re-indexing of all company portals in response to every user feedback, the system applies partial re-indexing only to the specific data sources and document types that generated the feedback. This selective approach maintains search relevance by updating only the necessary portions of the index, significantly reducing computational overhead compared to complete re-indexing operations.
Data Source
AI summary
A method, computer system, and computer program product for interactively locating information. Pages of organization information are identified from a number of company portals, websites, and online systems. The pages of organization information are indexed based on structural attributes of the pages and company relevant parameters. A search query is received from a natural language interface. The search query is received within a data context of the user in the organization. The search query is interpreted according to the data context of the user within the organization. A page of organization information is identified according to the interpreted search query. Responsive to identifying the page of information, the pages of organization information are re-indexed based on the search query, the data context, and feedback from the user regarding search results.