On-Demand Indexing for Search Completeness
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Solution Overview
Problem
In computerized systems with numerous variable objects, index-based searches may not be thorough due to the indexing process lagging behind, resulting in objects not being indexed or having incomplete information, which limits the search for related or relevant objects.
Innovation Solution
The indexing server identifies and indexes objects with properties similar to those already indexed, providing references to related objects and allowing for post-search indexing to extend the search results, with options to prioritize immediate indexing or schedule it for later.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the computerized system indexes all objects to ensure thorough search results, then the completeness of search results is improved, but the system load and indexing time increase significantly
Solution Approach 1:
The system performs partial indexing by identifying and indexing only those non-indexed objects that have properties similar to already indexed objects. This selective approach provides sufficient search completeness without the burden of indexing every single object in the system, thereby resolving the contradiction between search reliability and system productivity.
Solution Approach 2:
The system performs preliminary identification of non-indexed objects with similar properties before executing the full indexing process. By pre-selecting candidate objects based on property similarity to already indexed objects, the system prepares a targeted subset for indexing, reducing the overall indexing load while maintaining search thoroughness.
2Loss of information
If the system indexes non-indexed objects with similar properties immediately, then the search completeness is improved, but the indexing time and resource consumption increase
Solution Approach 1:
The system dynamically adjusts the indexing process by allowing users to choose between immediate indexing and scheduled indexing of non-indexed objects. This dynamic approach enables the system to adapt to different user needs and system conditions, providing search completeness when needed while managing indexing time and resource consumption flexibly.
Solution Approach 2:
The system implements periodic indexing by scheduling the indexing of non-indexed objects for later execution rather than performing it immediately. This periodic action allows the system to maintain search completeness while distributing the indexing load over time, thereby reducing peak resource consumption and indexing time impact on system performance.
3Measurement precision
If the system performs comprehensive indexing of all objects, then the accuracy of search results is improved, but the complexity of the indexing process increases
Solution Approach 1:
The system segments the indexing process into distinct phases: identifying already indexed objects, detecting non-indexed objects with similar properties, and indexing the detected objects. This segmentation simplifies the overall indexing process by breaking it down into manageable steps, reducing complexity while maintaining search accuracy through systematic property comparison and matching.
Data Source
AI summary
A method for indexing objects in a computerized system having an index, comprising identifying in the computerized system an at least one indexed object that meets an at least one criterion related to contents of the at least one indexed object, detecting an at least one non-indexed object having a property similar to an at least one property of the at least one indexed object that was identified, and indexing the at least one non-indexed object in the index, wherein the method is performed by the computerized system, and an apparatus for performing the same.