Multi-Index Search Engine Context Refinement
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Solution Overview
Problem
Search engines face challenges in balancing recall and precision, as optimizing for one metric often negatively impacts the other, and maintaining large-scale indexes is time-consuming and costly.
Innovation Solution
Implementing a multi-index search system that processes search queries through a primary general search index and secondary contextual search indices, allowing for context-based refinement of search results and frequent updates to improve relevance without compromising recall.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large-scale index is used to improve recall, then more relevant results are returned, but the time and cost to create and maintain the index increases
Solution Approach 1:
The patent divides the large-scale index into multiple smaller contextual indexes organized in a hierarchy. Each contextual index covers a specific context or domain, allowing the system to segment the monolithic index maintenance task into smaller, more manageable units that can be updated independently and more efficiently.
Solution Approach 2:
The patent implements a dynamic index structure where contextual indexes can be selectively updated based on changing search patterns and contexts. The system adapts by identifying frequently searched contexts and creating or updating corresponding contextual indexes dynamically, rather than maintaining all indexes statically.
2Measurement precision
If optimization is applied to improve precision, then more relevant results are returned, but fewer results are returned including relevant ones, thus lowering recall
Solution Approach 1:
The patent applies different optimization strategies to different contextual indexes based on their specific characteristics and the nature of searches within each context. Each contextual index can be tuned with context-specific parameters and algorithms, allowing local optimization without affecting global recall across all search contexts.
Solution Approach 2:
The patent introduces a query analysis component that acts as an intermediary between the user query and the search indexes. This component determines the appropriate context for the query and selects which contextual indexes to search, ensuring that optimization in one context does not negatively impact recall in other contexts.
3Measurement precision
If multiple contextual indexes are created to improve search relevance, then precision is enhanced, but device complexity increases
Solution Approach 1:
The patent designs a universal contextual index framework where a single multi-functional system handles diverse search contexts. The contextual index structure and query analysis mechanism serve multiple functions: categorizing queries, selecting appropriate indexes, and managing updates across different contexts, thereby reducing overall system complexity despite handling multiple specialized indexes.
4Reliability
If frequent updates are applied to contextual indexes to improve relevance, then current and relevant results are returned, but the complexity of index management increases
Solution Approach 1:
The patent implements a self-updating mechanism where the system automatically identifies when contextual indexes need updates based on search pattern analysis. The query analysis component monitors search behavior and automatically triggers index creation or updates when new contexts or patterns are detected, eliminating the need for manual index management decisions.
Data Source
AI summary
Systems and methods for performing multi-index searches are described in which a search string may be received, and processed by first running the query through a general search index, such as an Internet or e-commerce search. The results of the general search may then be analyzed to determine an appropriate context for the search query, e.g. clothing, sports, games, etc. The search query may then be processed using a second search index that is tuned to the specific context of the search query. After obtaining the results to the second search, the second search index and/or ranking algorithms may be modified to improve future search results having a similar context.