Search Relevance via Data Container Access Pattern Tracking
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Solution Overview
Problem
Conventional storage system search engines fail to determine the relevance of data containers containing search terms due to the lack of cross-linking between data containers, making it difficult to produce the most relevant search results.
Innovation Solution
A system and method that analyzes data container access patterns by tracking access information such as the number of users and frequency of access to rank search results, utilizing this data to improve the relevance of search outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines are used in storage systems, then search functionality is provided, but the relevance of search results cannot be determined due to lack of cross-linking between data containers
Solution Approach 1:
The system performs preliminary actions by tracking and recording access patterns to data containers before search operations are executed. This pre-collection of access information (number of accesses, unique users, time periods) enables the search engine to later determine relevance without requiring cross-linking between data containers, thus resolving the contradiction between providing search functionality and determining result relevance
Solution Approach 2:
The patent introduces an intermediary mechanism - the access pattern tracking system - that mediates between the storage system's lack of cross-linking and the search engine's need for relevance information. This intermediary collects and stores access metadata, which then serves as the basis for ranking search results by relevance, effectively bridging the information gap without requiring structural changes to the storage system
2Measurement precision
If data container access patterns are tracked to improve search relevance, then search result accuracy is enhanced, but system complexity increases
Solution Approach 1:
The system segments the complexity by separating the access pattern tracking function from the search engine function. The tracking component collects metadata about data container accesses (number of accesses, unique users, time periods), while the search engine uses this pre-collected data for ranking. This segmentation allows the search relevance improvement without requiring the entire system to become complex, as each component has a focused, simple function
Solution Approach 2:
The storage system essentially serves itself by automatically tracking its own access patterns without requiring external intervention or complex analysis systems. The access information is collected as a natural byproduct of normal operations, and this self-generated data is then used by the search engine to improve result accuracy, reducing the need for additional complex infrastructure
Data Source
AI summary
A system and method for improving the relevance of search results using data container access patterns. An indexing process tracks data access patterns and updates an access data structure. When executing a search operation, a search process first identifies a set of data containers containing the search terms. The search process then utilizes the access data structure to rank the identified data containers based on the collected data access pattern information.