Policy Driven Contextual Search for Database Efficiency
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Solution Overview
Problem
Current data search systems in large databases are inefficient and require specialized skills, as they rely on keyword searches, leading to laborious and error-prone processes for users seeking specific data sets.
Innovation Solution
Implementing a policy-driven contextual search method that allows users to apply pre-defined policies to refine search results, using a distributed data processing environment with a search application programming interface (API) and policy-driven contextual search extension (PCSE) to filter and recursively search data sets based on user-selected criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If keyword-based search is used in large databases, then search coverage is comprehensive, but search efficiency and ease of operation deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-defining search policies with common search criteria, filters, and parameters before users execute searches. Users can select from pre-configured policies rather than constructing complex search queries from scratch, which improves search efficiency while reducing the expertise required.
Solution Approach 2:
The patent introduces search policies as an intermediary layer between users and the database search function. These policies act as pre-packaged search configurations that mediate between user intent and complex search operations, making the search process easier to operate while maintaining comprehensive search coverage.
2Measurement precision
If contextual policies are applied to refine search results, then search accuracy and relevance improve, but device complexity increases
Solution Approach 1:
The search system is segmented into distinct components: search policies, policy parameters, and execution engine. Each policy is an independent, self-contained configuration that can be developed, stored, and executed separately. This segmentation allows the system to achieve high search accuracy through multiple policy layers while managing complexity through modular design.
Solution Approach 2:
The patent utilizes parameter changes by allowing dynamic modification of search policy parameters (such as date ranges, data sources, filters) without changing the underlying policy structure. This enables precise control over search results while maintaining a relatively simple policy framework, resolving the contradiction between accuracy and complexity.
Data Source
AI summary
In an approach to contextual search of electronic records, one or more computer processors receive a first search request from a user. The one or more computer processors send a plurality of first search results associated with the first search request to the user. The one or more computer processors receive one or more selected policies from the user, based, at least in part, on the plurality of search results. Responsive to receiving the one or more selected policies, the one or more computer processors apply the one or more selected policies to the plurality of first search results. The one or more computer processors generate a second search request based, at least in part, on the one or more applied selected policies. The one or more computer processors send a plurality of second search results associated with the second search request to the user.