Federation Engine Value Index for Search Targeting
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Solution Overview
Problem
Current meta search techniques face performance bottlenecks due to inefficient targeting of search engines and limitations in handling internationalization, as they often rely on pre-configured keywords that restrict searches to specific engines and are language-dependent, failing to comprehensively search across diverse data types and international databases.
Innovation Solution
A system and method that utilizes a federation engine to access and generate a value index from distribution data across multiple search engines, intelligently determining which engines to query based on search keywords, thereby optimizing search results by distributing queries to the most relevant engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pre-configured keywords are used to target search engines, then search performance is improved, but search comprehensiveness deteriorates because searches are limited to configured engines only
Solution Approach 1:
The system dynamically determines which search engines to query based on the search keywords and the value index, rather than using static pre-configured keyword-to-engine mappings. This allows the search engine selection to adapt flexibly to different search queries while maintaining performance optimization.
Solution Approach 2:
The system changes the parameter of search engine selection from fixed pre-configuration to dynamic determination based on keyword analysis and value index lookup. This enables the system to adjust which engines are queried based on the specific search request and available data distributions.
2Ease of operation
If pre-configured keywords are used for search targeting, then query processing is simplified, but internationalization capability deteriorates due to language-dependent keywords
Solution Approach 1:
The system extracts language-dependent keyword configuration from the search targeting mechanism. Instead of relying on pre-configured language-specific keywords, the system uses distribution data and value indices to determine search engine targeting, separating the targeting function from language-specific configurations.
Solution Approach 2:
The value index and distribution data mechanism provides universal search engine targeting that works across multiple languages and international databases. The same value index structure can serve different languages and regions without requiring separate pre-configuration for each language.
3Adaptability or versatility
If all queries are distributed to all search engines, then search comprehensiveness is improved, but system overhead and reaction time deteriorate
Solution Approach 1:
The system performs preliminary action by pre-building and maintaining the value index from distribution data across search engines. This pre-computed index enables fast lookup during actual search queries to determine which engines should be queried, avoiding the need to evaluate all engines for each query.
Solution Approach 2:
The system uses feedback from distribution data analysis to dynamically determine search engine targeting. The value index reflects the actual data distribution patterns, providing feedback that guides query routing to the most relevant engines, optimizing both comprehensiveness and performance.
4Measurement precision
If a value index is generated from distribution data, then search engine targeting accuracy is improved, but system complexity increases
Solution Approach 1:
The system creates a simplified copy of search engine data distribution characteristics in the form of a value index. This index is derived from distribution data but structured in a way that enables efficient lookup and decision-making during search queries, separating the complexity of data collection from the simplicity of query processing.
Data Source
AI summary
A method and system for searching data is provided. An index of a search engine is accessed. Distribution data is extracted from the index of the search engine. A value index is generated from the distribution data. A search request is received from a client. A query is generated based on the search request and the value index. The query is forwarded to the search engine for execution.